UK

United Kingdom · Technical roles · Mid-Level (2-5 years)

Knowledge Management Engineer

Here is the whole job, in plain words. What it is, a real day, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

  • Experience bandMid-Level (2-5 years)
  • Direct reportsNo direct reports
  • Reports toSenior Knowledge Management Engineer
  • UK framework levelUsually a coordinator, or early in a professional job

Also advertised as Technical Content Specialist · Information Architect (Junior) · Internal Documentation Engineer

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Knowledge Management Engineer

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

This role is all about making sure our engineers can find what they need, when they need it. You'll be the one building and looking after the internal knowledge bases, making sure they're actually useful and not just a graveyard for old documents. Think of it as being the librarian, but for highly technical stuff, and you get to build the library itself. It's a hands-on role, a bit of coding, a bit of content, and a lot of making things better for everyone else.

2What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Confluence / Notion (Knowledge Base Platforms)Intermediate

Managing content, permissions, and templates within existing spaces. You'll be creating new pages, reorganising sections, and ensuring content owners are using the right structures.

Elasticsearch / Algolia (Search & Indexing)Basic

Using the front-end search UI (e.g., Kibana for Elasticsearch) to run basic queries, check results, and understand search behaviour. You'll be looking for common failed searches.

Python (scripting for content ingestion/automation)Intermediate

Writing basic scripts using libraries like `requests` or `BeautifulSoup` to pull data from APIs or scrape internal sites for content ingestion, or to automate simple content health checks.

Google Analytics / Tableau (Analytics & Visualisation)Basic

Monitoring pre-built dashboards to track page views, popular search terms, and user engagement within your knowledge domains. You'll use this data to spot trends.

Jira / Slack / MS Teams (Collaboration & Ticketing)Intermediate

Configuring project integrations with our knowledge base, setting up basic notifications, and helping to manage support tickets related to knowledge content and platforms.

3What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing inWhere you are nowThe step above
Content Creation & UpdatesExecutes content updates based on specific requests; drafts new content under close supervision.Independently creates and updates content within assigned domains; proposes new content based on identified gaps; seeks review from SMEs.Defines content standards and templates; leads content strategy for major workstreams; reviews and approves junior team members' content.
Platform Configuration (within existing tools)Adjusts permissions or basic settings under guidance.Manages content permissions, templates, and space structures within existing instances; configures basic integrations (e.g., Jira-Confluence).Administers entire platform instances; designs complex macros and integrations; defines space architecture and governance.
Search OptimisationUses front-end search UI to test queries; reports on basic search results.Analyses search query logs to identify content gaps; suggests improvements to content or metadata for better search relevance.Writes and tunes complex Elasticsearch queries (DSL); configures index mappings; implements custom ranking models.
Automation & ScriptingRuns existing scripts; makes minor modifications under supervision.Writes basic Python scripts for data ingestion or content health checks; sets up simple automation workflows (e.g., Zapier).Develops robust, scheduled Python applications for ETL; builds custom API integrations; manages complex automation workflows.
Budget AllocationNo authority; escalates all spend requests.Recommends tool upgrades or small purchases (up to £1K); requires approval from Senior KM Engineer.Manages project budgets up to £50K; makes recommendations for larger tool investments or vendor contracts.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

Content Health Score
The percentage of pages within your owned knowledge domain that have been reviewed or verified within the last six months.
Target · >85% of pages reviewed/verified

If your domain has 100 pages, you'll aim to have at least 85 of them confirmed as accurate and up-to-date by their owners every six months. We'll track this automatically through our platform.

KM Support Ticket Resolution
The percentage of user-facing knowledge management support tickets (e.g., 'can't find X', 'this page is wrong') resolved within our 48-hour service level agreement (SLA).
Target · 95% of tickets resolved within 48 hours

If 20 tickets come in this week, you'll need to close 19 of them within two working days. This shows you're responsive and keeping the system running smoothly.

User Satisfaction (CSAT)
The average rating from users on 'Was this page helpful?' feedback widgets embedded in our knowledge base articles.
Target · Average of 4.5/5 stars

If 100 people rate a page, and the average score is 4.6, you're doing great. If it drops to 3.5, we'll need to dig into why that content isn't hitting the mark.

Search Query Success Rate
The percentage of internal search queries that result in a user clicking on a relevant result on the first page, indicating they found what they were looking for.
Target · Increase from 60% to 70% within 12 months

We'll look at the logs. If 100 searches happen and 60 result in a click on the first page, that's 60%. Your job is to make that number climb by tuning search and improving content.

Information Scent Improvement
How well users can intuitively navigate and predict where to find information, reducing frustration and aimless browsing.
  • Feedback from user interviews and usability tests consistently highlights ease of navigation. Fewer 'where do I find X?' questions in Slack. Observational studies show users quickly finding information without extensive searching or clicking through irrelevant links.
Content Quality & Clarity
The overall readability, accuracy, and completeness of the documentation you manage, making it genuinely useful for engineers.
  • Positive feedback from engineers on clarity and conciseness. Reduced instances of 'stale content' being reported. Content is free from jargon where possible, or clearly explains it. New joiners consistently refer to documentation for answers rather than asking peers.
Collaboration & Feedback Integration
How effectively you work with content owners and engineering teams to get their input and ensure documentation reflects current practices.
  • Regular, productive meetings with content owners. Timely responses to your requests for content review or updates. Evidence of feedback loops being implemented (e.g., user comments leading to content improvements). You're seen as a helpful partner, not just someone making demands.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy
Making a Tangible Impact on Productivity

You'll get a real kick out of seeing your work directly reduce the 'time-to-information' for engineers. Every time someone finds an answer quickly because of a system you built or content you organised, you'll feel that sense of accomplishment.

An engineer tells you they found a critical runbook in seconds during an incident, thanks to the improved search filters you implemented. That's a good day.

Bringing Order to Chaos

If you enjoy taking a messy, disorganised pile of information and turning it into a clear, navigable structure, you'll love this. It's about solving puzzles and creating systems that make sense.

You take a collection of disparate team wikis and merge them into a unified, logically structured knowledge base, complete with consistent tagging and clear navigation. The 'before' and 'after' will be hugely satisfying.

Continuous Learning & Problem Solving

This isn't a 'set it and forget it' role. You'll constantly be learning about new technologies, new team structures, and new ways to improve knowledge flow. Every 'can't find X' is a new problem to solve.

You discover a new search pattern in the logs, which leads you to research a different indexing strategy or a new way to structure content. You're always optimising and improving.

What frustrates people
  • The 'Ownership Hot Potato': Everyone agrees documentation needs an owner, but few want to be that owner, leaving you to chase people for updates.
  • Evangelism Fatigue: The constant, uphill battle of convincing brilliant engineers that writing things down is as important as writing code.
  • Garbage In, Garbage Out: You can build the world's best search engine, but it can't fix poorly written, ambiguous, or non-existent source material.
  • The ROI Justification Loop: Constantly having to prove the value of KM in 'hard' metrics (like reduced support tickets) to justify resources.
What this role does not give you
  • A purely coding-focused role: While scripting is involved, it's not a software engineering position.
  • A 'set it and forget it' environment: Knowledge management is continuous work; content decays, and systems need constant tuning.
  • Guaranteed immediate adoption: Changing habits takes time and persistence, even with great tools.

6Who you work with

This role directly impacts engineering productivity and efficiency by ensuring critical technical knowledge is accessible. It helps new hires get up to speed faster and reduces the burden on senior engineers who often answer the same questions repeatedly. Ultimately, it means we build better products, quicker, with less frustration.

Inside the business
  • Individual Engineering Teams (e.g., Mobile, Backend, SRE)
  • Product Managers (for feature documentation)
  • Technical Writers (for content standards)
  • IT Support (for internal tool documentation)
  • Learning & Development (for onboarding materials)

7What you need before you start

Not a wish list. The things you would be expected to already have.

  • At least two years of experience working with knowledge base platforms (like Confluence, Notion, SharePoint, or similar) in a technical environment.
  • Demonstrable experience in creating, editing, and managing technical content, even if it was informal documentation.
  • A basic understanding of scripting, preferably Python, for automating simple tasks or data manipulation.
  • Experience using internal search tools and an understanding of how they work at a basic level.
  • A proven ability to work collaboratively with technical teams and gather information from subject matter experts.
  • A genuine interest in making information more accessible and improving internal processes.

8What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Search Relevance Tuning

As our knowledge base grows, simple keyword searches won't cut it. Engineers will expect Google-like precision. You'll need to understand how to fine-tune our search engines to deliver highly relevant results.

Field Boosting · Synonym Lists & Stop Words · Query DSL (Domain Specific Language)

  • This quarter: Take an online course on Elasticsearch Query DSL or Algolia's search API.
  • Next quarter: Propose and implement a small change to our search configuration based on a common user complaint.
  • Month 6: Develop a system for regularly reviewing and updating synonym lists based on search log analysis.

Quick win: Start by analysing our top 10 'no results' search queries and see if adding a synonym or improving content tagging could fix them.

Data-Driven Content Strategy

Moving from reactive content creation to proactive, data-informed decisions. You'll use more advanced analytics to predict what knowledge is needed before engineers even ask for it.

Knowledge Gap Analysis · Content Performance Metrics · User Journey Mapping

  • This quarter: Work with the Senior KM Engineer to conduct a small-scale knowledge gap analysis for one engineering team.
  • Next quarter: Learn how to build a custom dashboard in Tableau or Power BI to visualise content performance metrics.
  • Month 6: Present a data-backed proposal for new content or a content reorganisation to an engineering team lead.

Quick win: Regularly review the 'top unclicked search terms' in our analytics. This is often a goldmine for identifying missing content.

9Staying current once you are in

What people here do to keep up
  • Regularly read industry blogs and articles on knowledge management, information architecture, and technical documentation best practices.
  • Attend webinars or online courses on specific tools in our tech stack (e.g., advanced Confluence features, Elasticsearch query tuning).
  • Participate in relevant online communities or forums to learn from peers and share experiences.
  • Seek out opportunities to present on knowledge management topics internally, sharing your insights and best practices with engineering teams.
  • Take on small, self-directed projects to experiment with new tools or AI applications in a KM context.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Prompt Engineering for Knowledge Work

Honestly, competitors are already using tools like GPT to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce peers. This isn't future-gazing; it's happening now.

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

Your PlanIllustration

Built for Knowledge Management Engineer

2 units that map to this job, from the qualifications that cover it.

  1. Producing Technical Information for Engineering ActivitiesExcellence, Achievement & Learning Limited · covers 2 of 6 standardsLevel 3
  2. Manage knowledge in own area of responsibilityCity and Guilds of London Institute · covers 2 of 6 standardsLevel 4
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering for Knowledge Work

Honestly, competitors are already using tools like GPT to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce peers. This isn't future-gazing; it's happening now.

  • Context Windows & Token Limits
  • Temperature Settings
  • Retrieval-Augmented Generation (RAG)
  • Output Validation & Hallucination Detection

What you’ll use

Skills this role draws on

Technical

  • Information Architecture (IA)
  • Taxonomy & Ontology Design
  • Content Lifecycle Management
  • Internal Search Optimisation
  • User-Centred Design (UCD) Principles

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Junior Technical Writer / Documentation Specialist

    2-3 years

    Skills to master

    • Clear technical writing, content structuring, understanding of audience needs, basic content management system (CMS) usage.

    You're ready to move on when

    • You're consistently writing clear, accurate documentation that engineers find useful.
    • You've started thinking about how content is organised, not just what's in it.
    • You're comfortable working with engineers to extract information.
  2. 2

    IT Support Engineer (with a focus on internal tools)

    3-4 years

    Skills to master

    • Troubleshooting internal systems, understanding user pain points, documenting solutions, familiarity with internal tools like Jira and Confluence.

    You're ready to move on when

    • You're often creating or improving internal knowledge base articles to deflect common support tickets.
    • You've noticed patterns in 'can't find X' questions and have ideas for better organisation.
    • You enjoy solving problems by making information more accessible.
  3. 3

    Software Engineer (with an interest in developer experience)

    2-4 years

    Skills to master

    • Coding skills (Python), understanding of developer workflows, empathy for user experience, desire to improve internal tooling.

    You're ready to move on when

    • You've built or contributed to internal developer tools or documentation platforms.
    • You're frustrated by poor internal documentation and have ideas on how to fix it.
    • You're keen to apply your technical skills to improve information flow rather than product features.

11Where this role leads

The long view:Your journey here isn't just about a job; it's about building a career in a field that's becoming increasingly critical for technical organisations. We're excited to see where you take it.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Knowledge Management Engineer is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

Where it leads

Roles this leads to

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Producing Technical Information for Engineering ActivitiesLevel 3

Applied to your work in Knowledge Management Engineer

The objective of this unit is to enable learners to produce accurate and clear technical information for engineering activities. Learners will gain the ability to gather information, produce documentation using appropriate formats and standards, and review it for errors, ensuring effective communication.

How the thinking builds
  1. Remember
  2. Understand
  3. Apply
  4. Analyse
  5. Evaluate
  6. Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

  1. Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
  2. What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
  3. The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
  4. How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
  5. Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Knowledge Management Engineer

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

  • Content Health ScoreThe percentage of pages within your owned knowledge domain that have been reviewed or verified within the last six months.If your domain has 100 pages, you'll aim to have at least 85 of them confirmed as accurate and up-to-date by their owners every six months. We'll track this automatically through our platform.>85% of pages reviewed/verified
  • KM Support Ticket ResolutionThe percentage of user-facing knowledge management support tickets (e.g., 'can't find X', 'this page is wrong') resolved within our 48-hour service level agreement (SLA).If 20 tickets come in this week, you'll need to close 19 of them within two working days. This shows you're responsive and keeping the system running smoothly.95% of tickets resolved within 48 hours
  • User Satisfaction (CSAT)The average rating from users on 'Was this page helpful?' feedback widgets embedded in our knowledge base articles.If 100 people rate a page, and the average score is 4.6, you're doing great. If it drops to 3.5, we'll need to dig into why that content isn't hitting the mark.Average of 4.5/5 stars
  • Search Query Success RateThe percentage of internal search queries that result in a user clicking on a relevant result on the first page, indicating they found what they were looking for.We'll look at the logs. If 100 searches happen and 60 result in a click on the first page, that's 60%. Your job is to make that number climb by tuning search and improving content.Increase from 60% to 70% within 12 months
These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Knowledge Management Engineer to Senior Knowledge Management Engineer, and whatever you decide comes after.

Level 3 · in progressAI Fluency→ Senior Knowledge Management Engineer→ your design
Where this takes you

Your journey here isn't just about a job; it's about building a career in a field that's becoming increasingly critical for technical organisations. We're excited to see where you take it.

See Your Progress GrowIllustration
Knowledge Management Engineer
  • Information Architecture (IA)
  • Taxonomy & Ontology Design
  • Content Lifecycle Management
  • Internal Search Optimisation
  • User-Centred Design (UCD) Principles
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

14The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Knowledge Management Engineer is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Senior Knowledge Management Engineer

    3-5 years

    L3

    • Advanced Information Architecture: Designing complex content models and navigation structures.
    • Search Engine Tuning: Writing and optimising complex Elasticsearch queries (DSL) and configuring index mappings.
    • API Integration: Building robust, scheduled Python applications for ETL and custom API integrations with KM platforms.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, knowledge management can sometimes feel like a never-ending battle against content decay and information overload. But what if you could offload the tedious, repetitive bits to AI? Imagine more time actually solving problems and less time on manual drudgery.

In this role, AI isn't here to replace you; it's here to be your co-pilot. We're talking about tools that can handle the grunt work, leaving you free to focus on the strategic, human-centric aspects of making knowledge truly useful. Here's a glimpse of how you'll use AI to make your daily work lighter and more impactful.

Automated Content Curation

Use AI to automatically scan new documents, suggest relevant tags from our taxonomy, and flag content that looks stale or duplicated. This means less manual tagging and more reliable content health scores, freeing you up from tedious auditing.

Intelligent Gap Analysis

Apply AI-powered topic modelling to search query logs. Go beyond simple keywords to identify the underlying themes and questions engineers are asking but can't find answers for. This gives you a data-driven backlog of exactly what new content is needed, saving you hours of manual analysis.

First-Draft Documentation

Use Large Language Models (LLMs) to generate initial drafts of technical documentation. Summarise complex design docs, convert code comments into user guides, or rephrase jargon-filled text for a wider audience. This helps overcome the 'blank page' problem for subject matter experts and gets content out faster.

Context-Aware Answer Bots

Help deploy and refine our internal Slack/Teams bot, powered by Retrieval-Augmented Generation (RAG). This bot answers natural language questions by pulling relevant snippets from the knowledge base and synthesising direct answers, deflecting repetitive questions from you and other engineers.

Common questions

Common questions

How do you become a Knowledge Management Engineer?

Common routes in include Junior Technical Writer / Documentation Specialist (2-3 years), IT Support Engineer (with a focus on internal tools) (3-4 years) and Software Engineer (with an interest in developer experience) (2-4 years). Times vary with prior experience.

Where can a Knowledge Management Engineer progress to?

This role can lead on to Senior Knowledge Management Engineer (3-5 years), depending on the skills you build.

What level is a Knowledge Management Engineer in the UK?

This role aligns to RQF Level 3 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Knowledge Management Engineer?

Increasingly, Prompt Engineering for Knowledge Work. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Knowledge Management Engineer, works on the job you actually do, and keeps going at your pace rather than a timetable's.

  • Searching and planning stay free. You only pay when you start learning.
  • Your credits are yours. Regulated, and they don't vanish when a subscription ends.
  • Cancel any time and billing stops. No notice period, no minimum term.

Your path, personalised

You have the map. Walking it is the part we do together.

This route runs to 6 national skill standards. That is a real journey.

Zavmo shapes a learning experience as unique as you are. It fits how you learn, your pace and the work you already do. Every step stays benchmarked to recognised national standards. That’s the plan for becoming a Knowledge Management Engineer: personal to you, and it still counts. The first steps are free.

Independent research finds well-designed intelligent tutoring performs nearly as well as one-to-one human tutoring: VanLehn (2011), Educational Psychologist.

A private tutor in the UK averages £35–40 an hour . Zavmo is £70/month.

A real plan on learn.zavmo.ai: Ofqual-regulated units, credits, and a three-month run at your own pace.
Start free No commitment. See your first steps free.

15Where to go from here

Other roles at Level 3

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

Other roles in Technical roles

Stay in the field you know and move sideways rather than up.

If you leave this industry

The skills you'll gain here—information architecture, search optimisation, content strategy, and technical communication—are highly transferable. You could move into roles like Product Manager for internal tools, UX Designer specialising in information flows, or even a more senior Technical Writer role in other tech companies. The ability to organise complex information is valuable everywhere.

Not sure this is the right direction?

Work out what you actually want from work first, then come back and see which roles fit it. Takes about ten minutes.

This role profile is © 2026Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.