BuildSomething.

Why it's good for your CV

Shows you can build a complete tool, handle file I/O, work with the terminal. Simple enough to finish in a weekend.

First steps

• Build the timer loop with Python's time module
• Log sessions to sessions.json with timestamps
• Add a --stats flag that shows weekly totals
• Publish to PyPI so anyone can pip install it

Effort (1–5)

Why it's good for your CV

Full CRUD app, database design, maybe a simple API. Shows you can think in data models, not just scripts.

First steps

• Define your schema: applications, contacts, notes tables
• Build add / list / update commands or routes
• Add status filter (applied / interview / rejected / offer)
• Optional: email reminder when follow-up date passes

Effort (1–5)

Why it's good for your CV

AI-powered tool using real APIs. Every developer needs this — great for stars and visibility. Killer talking point in interviews.

First steps

• Use GitHub API to fetch repo file tree + key files
• Send to Claude/OpenAI API with a structured prompt
• Output a formatted markdown README
• Add CLI flags: --format, --tone, --lang

Effort (1–5)

Why it's good for your CV

Combines LLMs, file parsing, and an external API. Directly useful — students and researchers will actually use this.

First steps

• Use pdfplumber to extract text from PDFs
• Prompt an LLM to extract Q&A pairs in JSON
• Export to .apkg format using genanki library
• Bonus: build a simple web UI with drag-drop PDF

Effort (1–5)

Why it's good for your CV

API integration, data aggregation, visualization. Shows you can build tools that people actually open every morning.

First steps

• GitHub GraphQL API for commit history and streak data
• Build a local Flask/FastAPI server to serve the dashboard
• Use Chart.js or Recharts for contribution graphs
• Add a daily goal tracker with localStorage or SQLite

Effort (1–5)

Why it's good for your CV

Web scraping, scheduling, email APIs, database. Clean problem. Everyone immediately understands the use case when you explain it.

First steps

• Use requests + BeautifulSoup to scrape product price
• Store URL, target price, current price in SQLite
• Schedule with cron or APScheduler
• Send alert via Gmail SMTP or SendGrid API

Effort (1–5)

Why it could make money

Students panic before job applications. £3–5 one-time payment. Low cost to run. Market is huge and always refreshing with new graduates.

How to build the MVP

• PDF upload → extract text → send to Claude with a recruiter persona prompt
• Return structured feedback in sections: Summary, Experience, Skills, Red flags
• Gate behind a £3 Stripe payment before showing results
• Launch on Twitter, Reddit r/cscareerquestions, university Discord servers

Effort (1–5)

Why it could make money

Developer tools convert well. You could ship this as a VS Code extension (free), then sell the API key for power users. Low churn — people integrate it into workflow and forget to cancel.

How to build the MVP

• Simple web form: paste diff → generate message
• Prompt engineering: conventional commits format, scope detection
• Add VS Code extension wrapper around the API
• Post on Hacker News "Show HN" — developers love this

Effort (1–5)

Why it could make money

B2B angle: sell to student unions and universities as a tool. One deal = thousands of users. You understand the problem from the inside.

How to build the MVP

• Simple profile: uni, modules, schedule availability
• Basic matching by module overlap
• In-app messaging or just share Discord/WhatsApp
• Test at your own uni first — 100 users who know you

Effort (1–5)

Why it could make money

Newsletter writers spend hours looking for sponsors. Charge £30/month to save them 5 hours. 50 customers = £1,500/month recurring.

How to build the MVP

• Intake form: niche, audience size, subscriber demographics
• Scrape affiliate networks (CJ, ShareASale) for relevant programs
• Generate personalized outreach email templates per sponsor
• Find first customers on Twitter / Beehiiv / Substack communities

Effort (1–5)

How to get your first client

Post in your uni Discord, career Facebook groups, Reddit r/cscareerquestions. Offer the first 3 for free in exchange for a testimonial screenshot.

Your process

• Client fills intake form (target role, industries, experience)
• Use Claude with strong prompts to draft headline, about, experience bullets
• You edit, personalize, quality check
• Deliver in 48h. Upsell: CV rewrite for £75 extra

Effort (1–5)

Where to find clients

Local businesses, family contacts, Upwork, Fiverr for the first 2–3 jobs to build reviews. Ask in local business Facebook groups: "what's your most boring weekly task?"

Example projects

• Auto-generate monthly PDF invoices from a spreadsheet
• Scrape competitor prices daily into a Google Sheet
• Auto-post to social media from a content calendar
• Send weekly email reports from a database query

Effort (1–5)

How to start

Post on Reddit r/learnprogramming, r/cscareerquestions, your uni Discord. Offer a free 30-min trial session. Two paid sessions per week = £160+ extra with zero setup cost.

What you offer

• LeetCode problem walkthroughs tailored to target company
• Behavioral question prep (STAR method)
• CV and GitHub portfolio review as add-on
• Written feedback notes after each session

Effort (1–5)

Why this matters for your career

Recruiters google you. A Twitter presence showing you build things publicly is worth more than a dozen applications. Takes 1 hour per week. Compounds massively over 6–12 months.

Content formula

• Thread 1: "I'm building X. Here's why and my plan."
• Weekly updates: what I built, what broke, what I learned
• Milestone posts: "shipped it. here's the repo." with screenshots
• Learnings posts: "I spent 3 hours debugging this. Here's what it was."

Effort (1–5)

How this compounds

Google indexes your posts. Someone searches "how to scrape Amazon prices Python 2025" — they find your post. You get traffic, credibility, and sometimes job offers from people who read your writing.

First 5 posts to write

• "How I built [your project] and what I learned"
• "[Error you spent hours on] — here's the fix"
• "My honest review of the IBM Data Science certificate"
• "How I structure my study sessions for uni + side projects"
• "5 Python scripts I use every week"

Effort (1–5)

Real demand

Startups and agencies are desperate for this. They know AI could save them time but don't know how to use it well. Your IBM AI courses give you credibility immediately.

How to sell it

• Post on LinkedIn: "I help businesses get 10x better results from ChatGPT/Claude"
• Offer a free prompt audit: find 3 ways their current AI use could be better
• Deliver: custom prompt library + documentation + usage guide
• Upsell: monthly retainer to maintain and improve prompts as their needs change

Effort (1–5)

Who to target

Small e-commerce shops, local restaurants, anyone running ads who doesn't understand their data. They want to know: "what's working, what should I stop?"

Your deliverable

• Clean the data with pandas, handle missing values
• 2–3 key visualizations (sales trends, customer segments, top products)
• 1-page PDF summary: "3 things your data is telling you"
• Optional: Jupyter notebook they can rerun themselves

Effort (1–5)

Why this is underrated

Most adults are terrified of technology. You can charge more than you think. It also sharpens your own knowledge — teaching forces you to understand things deeply.

How to get students

• Post flyers at local library, coffee shops, community centres
• List on Superprof, Tutorful, or local Facebook groups
• Offer to run a free "Intro to Python" session at a library
• Email local secondary schools — some pay for after-school sessions

Effort (1–5)

Why build this

You'll use it yourself every day. Perfect first bot — teaches webhooks, scheduling, and stateful conversations. Publish it and other students will use it too.

First steps

• Create bot with @BotFather, get token
• Use python-telegram-bot library with APScheduler
• Store user responses in SQLite
• Weekly stats message every Sunday: "You completed 5/7 days"

Effort (1–5)

Why build this

Language learning apps are a huge market. Start with one language, expand. Could eventually charge £2/month. 500 users = meaningful side income.

First steps

• Curate or scrape a word list with definitions and examples
• Send 3 words daily at chosen time per user preference
• Quiz mode: hide definition, user types answer
• Track streak and accuracy per user in SQLite

Effort (1–5)

Why build this

Personal finance tools are evergreen. The Telegram interface removes all friction — people already have it open. Great portfolio piece showing NLP + database design.

First steps

• Parse natural language: amount + category from free text
• Store entries in SQLite with user_id, amount, category, timestamp
• /report command: monthly totals per category as formatted message
• Optional: export to CSV on request

Effort (1–5)

Why build this

Staying current with the ecosystem is a real problem for developers. Solve it. This is also a great way to find projects to contribute to — turning learning into portfolio.

First steps

• GitHub Trending scraper or use GitHub Search API with date filter
• User sets preferences: languages, topics, min stars
• Format: repo name, description, stars, link — clean and scannable
• Let users save repos with /save command

Effort (1–5)

Why build this

Active recall is proven to be the best study method. Most students don't do it because making flashcards is tedious. This removes the friction completely.

First steps

• User sends text or PDF → extract content
• LLM generates Q&A pairs in JSON
• Bot asks questions one-by-one, awaits answer
• Grades with explanation, tracks weak topics over sessions

Effort (1–5)

Why build this

Early applicants get hired more often. This is a tool you'll personally use while job hunting. Others will want it. Could monetize at £5/month for custom filters.

First steps

• Scrape jobs with BeautifulSoup or use a jobs API (Adzuna, Reed API are free)
• Store seen job IDs to only send new listings
• /set command: keywords, location, job type
• Run on a free VPS or Railway.app

Effort (1–5)

Why build this

Every student group has this problem. University societies would use this. Could expand to workplace teams. Real-world scheduling logic is great to have on a CV.

First steps

• Group members submit available time slots via inline keyboard
• Algorithm finds overlap (intersection of availability sets)
• Announce the chosen time, set reminder 30 min before
• Optional: Google Calendar integration for invite generation

Effort (1–5)

Why build this

You're building this for yourself. The twist — showing your own goals instead of a hard wall — is genuinely more effective psychologically. And it's a great first extension.

First steps

• manifest.json with declarativeNetRequest or webRequest permission
• User inputs blocked sites and focus hours in popup
• Redirect to a custom "goals" page instead of hard block
• "Let me through anyway" button with 10-second delay + counter

Effort (1–5)

Why build this

You'll use this yourself when job hunting. Other students will want it. Could be your first Chrome Web Store listing. Simple DOM scraping + storage is easy to learn.

First steps

• Content script detects LinkedIn job pages, extracts title + company
• Click the extension icon → "Log this application"
• Store in chrome.storage.local with timestamp and status
• Popup shows list: applied / interview / rejected / offer

Effort (1–5)

Why build this

LLM-powered extensions are hot right now. This is the simplest possible one. Great intro to calling APIs from an extension. Easy to expand: translate, explain jargon, cite sources.

First steps

• Content script extracts main article text (use Readability.js)
• Popup triggers API call with extracted text
• Show streaming response in the popup panel
• Save summaries to chrome.storage for later reading

Effort (1–5)

Why build this

Dark Mode Reader has millions of users. You could build a better one. CSS injection + content scripts are fundamental extension skills. Huge potential audience.

First steps

• Inject CSS filter: invert(1) hue-rotate(180deg) on body
• Fix images and videos (re-invert them)
• Per-site on/off toggle stored in chrome.storage.sync
• User can tweak brightness and contrast via popup sliders

Effort (1–5)

Why build this

Developers and learners will love this. It's niche enough to find an audience quickly. Posting on r/learnprogramming could easily get you 1,000 installs in a week.

First steps

• Content script detects Stack Overflow code blocks
• Inject "Explain this" button next to each code block
• On click: send code to LLM with "explain like I'm learning" prompt
• Show explanation in a clean side-panel or inline dropdown

Effort (1–5)

Why build this

The reading time estimate is easy. The analytics layer on top is what makes it special. Could monetize the dashboard as a web app companion for £3/month.

First steps

• Extract article text, calculate word count ÷ 200 wpm = reading time
• Inject a subtle "X min read" badge near the article header
• Track scroll depth and time-on-page per article domain
• Weekly popup report: top sites, total reading time, estimated words read

Effort (1–5)

Why build this

Instantly relatable to every developer. Simple to build. Your dotfiles repo itself becomes a portfolio artifact showing your dev environment taste and discipline.

First steps

• Script reads a config file listing source → destination pairs
• Creates symlinks with error handling if target already exists
• --dry-run flag to preview what would happen
• Backup existing files before overwriting

Effort (1–5)

Why build this

Real-world data processing with pandas. You'll actually use it. Every person with a bank account is a potential user. Privacy-first angle resonates strongly.

First steps

• Parse CSV from major UK banks (Monzo, Starling export formats)
• Rule-based categorizer: keywords → categories
• Monthly report: spending per category, income vs expenses, savings rate
• Optional: plot with matplotlib — visual always impresses

Effort (1–5)

Why build this

Building a library (not just a script) shows a higher level of engineering thinking. Decorators, thread safety, and retry logic are all interview-relevant skills.

First steps

• @rate_limit(calls=10, period=60) decorator using threading.Semaphore
• @retry(max_attempts=3, backoff=exponential) decorator
• Combine both into @api_call(rate=10, retries=3)
• Write proper tests with pytest. Publish to PyPI.

Effort (1–5)

Why build this

Understanding how static site generators work is foundational web knowledge. Building one from scratch shows you understand the full stack. Use it for your own blog.

First steps

• Parse markdown with python-markdown, extract frontmatter with PyYAML
• Jinja2 templates for HTML generation
• Build index page with post list, tag pages
• Generate RSS feed XML. Deploy output folder to GitHub Pages.

Effort (1–5)

Why build this

Information retrieval is a core CS concept. Building it shows algorithmic thinking. Interviewers at tech companies love seeing this. Excellent for a data science or backend role.

First steps

• Simple web crawler with requests + BeautifulSoup, respect robots.txt
• Build inverted index: word → list of (doc_id, frequency) pairs
• TF-IDF scoring for ranking results
• Simple CLI or Flask UI to query the index

Effort (1–5)

Why build this

Using the Rich library for terminal UI shows you care about UX even in CLI tools. The contribution grid is visually impressive for a command-line app. Great README screenshot.

First steps

• Define habits in a YAML config file
• Daily check-in: mark each habit done/skipped
• Store in SQLite with date, habit, status
• Use Rich to render a colour-coded streak calendar grid

Effort (1–5)

Why build this

Combines data collection, NLP, and visualisation — three skills in one project. Perfect for an IBM Data Science portfolio. Employers see applied ML immediately.

First steps

• Reddit API (PRAW) to collect posts on a topic
• VADER or HuggingFace transformers for sentiment scores
• Store time-series sentiment data in SQLite
• Streamlit dashboard: line chart of sentiment over time, word cloud

Effort (1–5)

Why build this

Classic first web project done right. Shows you understand HTTP redirects, database design, and simple web APIs. Deploy it on Railway for free and use the URL in your CV.

First steps

• POST /shorten: store URL + random 6-char code in SQLite
• GET /{code}: redirect to original URL, log click with timestamp
• Simple HTML form frontend
• Analytics endpoint: clicks per link, clicks over time

Effort (1–5)

Why build this

Immediately useful. Shows AI API integration with practical product thinking. Perfect portfolio piece because everyone interviewing will want to use it.

First steps

• Paste job description into CLI or simple web form
• Prompt LLM: extract key skills and responsibilities, generate questions per category
• Output: technical Qs, behavioural Qs, company-specific Qs
• Optional: generate model answers for each question

Effort (1–5)

Why build this

You're building the tool that helps you build other tools. Meta and useful. Sharing this in developer communities will get you attention and stars quickly.

First steps

• GitHub Search API: issues with label "good first issue" + language filter
• Filter by: language, topic, repo stars, days since last activity
• Clean web UI or CLI output sorted by "easiest to contribute"
• Save interesting issues to a watchlist

Effort (1–5)

Why build this

Clean NLP project. TF-IDF cosine similarity is a must-know algorithm for data science roles. Add a simple Streamlit UI and it becomes a deployable web app in an afternoon.

First steps

• TF-IDF vectorization with scikit-learn
• Cosine similarity between document vectors
• Sentence-level breakdown: highlight matching sentences
• Streamlit UI: paste two texts, see score and highlighted comparison

Effort (1–5)

Why build this

Graph databases, NLP entity extraction, and D3.js visualisation in one project. Shows you can build complex, interconnected systems. Genuinely impressive portfolio piece.

First steps

• Parse markdown files, extract [[wikilinks]] and headings
• Build a graph: nodes = notes, edges = links between them
• Export graph as JSON for D3.js force-directed visualization
• Optional: use spaCy to extract named entities as additional nodes

Effort (1–5)

Why build this

Every developer who joins a new project needs this. Great stars potential. Shows you can combine static analysis with LLMs thoughtfully. Real engineering challenge.

First steps

• Clone repo, walk directory tree, filter by extension
• Use Python's ast module to extract functions, classes, imports
• Send file summaries + dependency info to LLM for synthesis
• Output: architecture overview + file-by-file guide in markdown

Effort (1–5)

Why it could make money

Freelancers and sales teams send hundreds of cold emails. Personalization is proven to 3–5x reply rates. £20/month for 100 personalizations. 100 users = £2,000/month.

How to build the MVP

• Input: company URL. Scrape homepage + About page + recent news
• LLM generates 3 personalized opening line variations
• User picks one, copies it. Track which variations get replies
• Free tier: 10 emails. Paid: unlimited

Effort (1–5)

Why it could make money

Notion templates sell consistently. Students are your perfect market — you understand their needs. Sell on Gumroad, Notion's own marketplace, and Reddit. Zero ongoing cost.

What to make first

• University study planner: weekly schedule + exam countdown + topic tracker
• Project portfolio tracker: GitHub project status + next steps
• Job application dashboard: pipeline view + interview notes
• Post on r/Notion, r/productivity, r/cscareerquestions

Effort (1–5)

Why it could make money

Solo developers and small teams can't afford senior code review. £15/month for unlimited PR reviews. Developer tools have excellent LTV. Strong B2B angle for small agencies.

How to build the MVP

• GitHub App that triggers on PR creation/update
• Send diff to LLM with a code review persona prompt
• Post review as a GitHub comment with inline suggestions
• Learn from accepted vs rejected suggestions over time

Effort (1–5)

Why it could make money

This exists but the implementations are inconsistent. If you build a reliable version for specific frameworks (Tailwind, Bootstrap), freelance developers will pay £10/month gladly.

How to build the MVP

• Image upload → base64 encode → send to Claude claude-opus with vision
• Prompt: "Convert this UI to clean Tailwind HTML. No placeholders."
• Show side-by-side: screenshot | generated code | live preview
• Let user choose: vanilla CSS, Tailwind, Bootstrap

Effort (1–5)

Why it could make money

Every company has too many meetings. Structured summaries save hours. £20/month per user for unlimited meetings. Sell to small teams — one decision-maker approves it.

How to build the MVP

• Audio: OpenAI Whisper API for transcription
• Text: send transcript to LLM with structured extraction prompt
• Output: Decisions / Action Items / Discussion / Next meeting
• Email the summary to all attendees automatically

Effort (1–5)

Why it could make money

Any developer shipping software needs changelogs. The pain is real. £10/month per repo. Open-source maintainers and indie hackers are the ideal early adopters.

How to build the MVP

• GitHub API: fetch commits between two tags or date range
• LLM: group commits by type (fix/feature/breaking), write user-friendly descriptions
• Output: markdown formatted keep-a-changelog compatible file
• One-click publish to GitHub Releases

Effort (1–5)

Why it could make money

Every student is overwhelmed. A scientifically-backed timetable they didn't have to build themselves? £5/term is nothing. Target 10,000 students = £50k recurring.

How to build the MVP

• Intake form: subjects, exam dates, difficulty ratings, fixed commitments
• Constraint satisfaction algorithm: spread subjects, prioritise by urgency
• Output: downloadable iCal file + printable weekly grid
• Launch on student Facebook groups, uni Reddit pages

Effort (1–5)

How to get clients

Every local business has a FAQ page. That FAQ is your chatbot script. Walk in, show them 5 minutes of their own bot answering questions, close the deal on the spot.

Your process

• Collect FAQ and product info from client website
• Build flow in Voiceflow or use OpenAI Assistants API
• Embed on their site with one script tag
• Monthly maintenance retainer: £50/month

Effort (1–5)

How to find clients

Every business with Excel reports is a prospect. Accountants, marketing agencies, property managers. "What reports do you make manually every month?" is your qualifying question.

Your process

• Understand their current Excel workflow and what they track
• Build Streamlit or Plotly Dash app reading from their updated CSV/Excel
• Deploy on Streamlit Cloud (free) with password protection
• Offer monthly hosting + update plan for £75/month

Effort (1–5)

Where the work is

Small businesses paying Zapier £300+/month for basic integrations they could have scripted once for £200. You're cheaper and the solution is permanent, not a monthly subscription.

Common requests

• Typeform → Notion database when form submitted
• Shopify order → send custom email via Mailchimp
• Google Sheets → auto-generate invoices in FreshBooks
• Instagram post → auto-tweet and schedule LinkedIn

Effort (1–5)

How to find clients

Photography students, art students, graphic design graduates — they all need portfolios. Post in creative Facebook groups, art school Discord servers, Instagram.

Your process

• Template-first: build 3 clean templates once, customize per client
• Client sends content via Google Form: bio, images, social links
• Deploy on Netlify (free) with their custom domain
• Upsell: SEO setup, Google Analytics, monthly updates

Effort (1–5)

Why this works

Most small businesses know they need SEO but have no idea where to start. A concrete prioritized action list is incredibly valuable. Low effort once you have a template.

Your process

• Screaming Frog free: crawl issues, broken links, missing metadata
• Google PageSpeed Insights: performance scores
• Ahrefs/Semrush free tier: keyword gaps, backlink overview
• Template report: Critical / Important / Nice-to-have sections

Effort (1–5)

Why this compounds

Each video is a portfolio piece, a learning reinforcement, and an audience-building asset. At 1,000 subscribers YouTube monetizes. Before that, it gets you job interviews.

Video ideas to start

• "I built a Telegram bot that tracks my expenses (full tutorial)"
• "Chrome extension from scratch in 1 hour"
• "My first open source contribution — how I found the issue and fixed it"
• "Building a job application tracker with Python and SQLite"

Effort (1–5)

How to grow it

Post each issue on Reddit, HackerNews, LinkedIn. Consistent niche newsletters grow by word of mouth. At 1k subscribers developers-focused sponsors pay £100–500 per issue.

The format (simple, sustainable)

• One tool you discovered this week
• One GitHub repo worth starring
• One tutorial or article worth reading
• One thing you learned building your project
• One question for the reader to think about

Effort (1–5)

Why LinkedIn specifically

Technical educators on LinkedIn get massive reach because most posts are career fluff. A clear, visual technical explanation stands out. Recruiters see it. Peers share it.

Post formats that perform

• "X things I wish I knew about [concept] when I started"
• "[Technology] explained with a pizza analogy" (visuals help)
• "I built [project] this weekend. Here's what I learned."
• "The one mistake I kept making with [language feature]"

Effort (1–5)

Why this works now

The dev TikTok space is much less saturated than general content. One viral video can add 10,000 followers. Those followers become newsletter subscribers and client leads.

Video ideas

• "This Python one-liner replaced 10 lines of code"
• "The Git command I use every single day"
• "What actually happens when you type a URL"
• "Explain your code to a rubber duck — this actually works"

Effort (1–5)

How to position it

You're an editor, not a ghostwriter. You improve clarity, structure, and argument strength. Students doing their own work but wanting to polish it before submission. Ethical and legal.

Your process

• Student sends essay + rubric + target grade
• Run through AI tools for structural analysis
• Add detailed inline comments and suggestions via Google Docs
• Turnaround in 24 hours. Bundle: 3 essays for £100

Effort (1–5)

Why this is powerful

Make it once, sell it forever. 100 sales at £25 = £2,500 with zero extra work. Each course also proves your expertise when you apply for jobs or clients. Double value.

How to make it fast

• Outline 6–8 short lessons, 10–15 minutes each
• Record on Loom (free) — no fancy equipment needed
• Host on Gumroad, Teachable, or Notion (cheapest)
• Price at £19 to start, raise price as reviews come in

Effort (1–5)

Why this is underrated

Most people don't know this exists. Bounties are public, the problem is defined, the codebase is real. Every bug you fix is a contribution you can cite in interviews. Money is a bonus.

How to start

• Browse IssueHunt.io and BountySource for issues in languages you know
• Start with smaller bounties (£30–80) to build track record
• Fork → fix → PR → reference the bounty issue in your PR
• Each completed bounty = real open-source contribution on CV

Effort (1–5)

How to get started

The first 5 reviews are everything on Upwork. Bid only on small jobs (£20–50). Win them fast, overdeliver, get 5-star reviews. Then raise your rate. Takes 2–3 weeks to gain traction.

Jobs to target first

• "Fix a bug in my Python script" — under 1 hour, £20–40
• "Scrape this website into a CSV" — under 2 hours, £30–60
• "Write a script to automate this task" — clear scope, easy to deliver
• "Help me understand why my code isn't working" — tutoring, £20/hour

Effort (1–5)

Why this works

The AI tools space is exploding and most reviews are garbage. Honest, technical reviews from someone who actually built things with the tools will be trusted and shared. Trust = conversions.

How to monetize

• Sign up for affiliate programs: Claude, Cursor, Notion AI, Jasper, etc.
• Review one tool per week with actual use cases from your projects
• Each review contains your affiliate link
• As list grows: sponsored reviews at £100–500 per issue

Effort (1–5)

Why it could make money

Government and financial APIs are notoriously painful to work with. A clean wrapper that just works is worth paying for. 50 customers at £10/month = £500 recurring. Very low churn once integrated.

How to build the MVP

• Pick one painful API (Companies House is a good UK example)
• Wrap it in a clean FastAPI endpoint with simple auth
• Document it properly — documentation IS the product for developers
• Charge via Stripe, manage API keys per customer

Effort (1–5)