Up nextLock In Technical Decisions Before AI Makes Them for YouDesign a Feature AI Can Execute Without Guessing · Lesson 2 of 7
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Product EngineerStep 3 of 9 · Plan before it builds
Spec a Product
OpenSpec
Design a Feature
Build Features
Review AI Code
This week on your RadarWeek of Oct 5
Versus · 4 min readJev vs LLMs
TLDR · 3:38What is Jev?
TLDR · 5:04Practical Jev Demo
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LiveSpec-Driven Development: From Idea to Production with AI
AG
Generative UI: Building Apps That Compose ThemselvesAlex Garrett-Smith
AG
Code Review at Agent ScaleAlex Garrett-Smith
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Spec Generator Skill
Turn a vague idea into a detailed product spec
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Docs WriterAgent
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The briefing · 2:35
RoleLive
Product Engineer
Own what gets built and how, end to end, with agents doing the typing.
Plan before it buildsSpec a ProductOpenSpecDesign a Feature
Build and shipBuild FeaturesReview AI CodeMerge and Deploy
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WorkflowSpec a Product Before AI Builds It33 min
WorkflowBuild Features with an AI Agent1 hr 38 min
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Deep diveContext Engineering for Coding Agents23 min
Full courseRAG for Real-World AI Applications4 hr 20 min
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Skills, starters and templates from the courses. Install in one line.
CollectionUnlearn Skills
13 skills for planning, review and shipping, from spec generation to a pre-commit ship gate.
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github.com/unlearndev/skills · ★ 82
Spec GeneratorTurn a vague idea into a detailed product spec
Skill
Code ReviewReview staged changes or a specific area of the codebase
Skill
Ship GateScan the staged diff for secrets, debug code, and stray files and return a straight PASS or BLOCK
Skill
ZombiesSuggest the most relevant tests to write for a feature using the ZOMBIES heuristic
Skill
Judge ArchJudge a branch's changes against the design decisions in the repo's DECISIONS.md
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TriageGroup a branch's changes into feature areas and assign risk tiers
Skill
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Spec Auditor PlusPaste a spec and get an audit of what an agent would have to guess
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Unlearn plugin for Claude CodeEvery Unlearn skill, the Docs Writer agent and the Ship Gate hook in one install
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RadarWeek 41 · Oct 5 to 11, 2026
This week's noteThe model stack is getting specialised
AI development has been built around one assumption: give a model some context and ask it to generate something. This week, we've seen more signs that the model stack is getting specialised.
AGAlex Garrett-Smith · Oct 9
Versus · 4 min readJev vs LLMs
TLDR · 3:38What is Jev?
TLDR · 5:04Practical Jev Demo
In this issue
VersusJev vs LLMs
TLDRWhat is Jev?
TLDRPractical Jev Demo
Blog postYou Don't Need an LLM for Everything
Coming to Radar
This Week in AI Dev
The Unlearn Podcast
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Building Agent SkillsDeep dive5 lessons29m
Context Engineering for Coding AgentsDeep dive6 lessons23m
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Courses5 courses · 65 lessons
The Future Proof DevFull course11 lessons1h 7m
Turbo ModeFull course13 lessons2h 22m
RAG for Real-World AI ApplicationsFull course30 lessons4h 20m
Building Agent SkillsDeep dive5 lessons29m
Context Engineering for Coding AgentsDeep dive6 lessons23m
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AGENTS.md StartersRule file
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Spec a Product Before AI Builds ItWorkflow10 lessons33m
Spec-Driven Development with OpenSpecDeep dive9 lessons56m
Design a Feature AI Can Execute Without GuessingWorkflow7 lessons24m
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AI for UI Design and Automated TestingFull course29 lessons2h 31m
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First FiveSkill
TriageSkill
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Merging and DeployingWorkflow8 lessons37m
Debugging and PerformanceWorkflow9 lessonsabout 29m
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Product Engineer › Spec a Product Before AI Builds It › Lesson 3 of 10
0:44 / 2:47CC
Lesson 3 of 10Shaping the Specification
In this lesson, you'll take your rough specification and turn it into something far more solid by removing assumptions, adding missing details.
## Users and roles
- Customers submit ideas and vote
- Team members review ideas- Admins manage team members- Team: reviews, comments internally, changes status
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Spec a Product Before AI Builds It
Workflow2 of 10 done
Why Planning Beats Vibe Coding4:05
Turn a Vague Idea Into a Structured Spec6:27
Shaping the Specification2:47
Give AI Technical Constraints from Day One1:17
Tell AI What It's Not Allowed to Build2:48
5 more lessons
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Lesson 3 of 10Shaping the Specification1:08 / 2:47
Use in this lesson
Repounlearndev/feedbackpitSkillSpec Generator
Prompt
Read spec.md and list every assumption it makes about users, roles and data. For each one, ask me the question that would remove it. Don't rewrite the spec yet.
Here's a permissions check AI generated. It compiles, it passes linting, it looks production-ready.
TSpermissions.ts+6+2-10 of 3 found
1export async functiongetUserPermissions(userId: string) {2const user = await db.query(3 FROM users WHERE id = );4const permissions = .flatMap((role) => role.permissions);5return [...new Set(permissions)];6}
11export async functiongetUserPermissions(userId: string) {22const user = await db.query(3-`SELECT * FROM users WHERE id = ${userId}`);3+'SELECT id, roles FROM users WHERE id = $1', [userId]);4+if (!user) return [];45const permissions = user.roles.flatMap((role) => role.permissions);56return [...new Set(permissions)];67}
Three issues hide in here. Hover each to see why it matters.
SQL injectionL3
String interpolation in a query. Safe today if the input is internal, a vulnerability the moment someone calls this function differently.
Fix
-`… WHERE id = ${userId}`);+'… WHERE id = $1', [userId]);
A real PR has hundreds of decisions just like these, each one context the model didn't have and you do. Catching bad code is only the start. The same judgment matters when you scope features, steer an implementation, or build the guardrails that stop these issues before they happen.
Radar
What changed this week, and what's worth your time. Free for everyone.
Week 41 · Oct 5 to 11, 2026
The model stack is getting specialised
AI development has been built around one assumption: give a model some context and ask it to generate something. This week, we've seen more signs that the model stack is getting specialised.
Alex Garrett-Smith · Oct 9
TLDRWhat is Jev?
ComparisonJev vs LLMs
BlogYou Don't Need an LLM for Everything
Deep diveContext Engineering for Coding Agents
Comparison · 4 min read
Jev vs LLMs
Jev was faster and cheaper than an LLM judge in OpenRouter's benchmark. Try it for one decision with a fixed set of answers.
TLDR · 3:38
What is Jev?
Jev is a model built to decide, not generate, so you hand it state and a typed question and get probabilities back.
TLDR · 5:04
Practical Jev Demo
Jev returns a probability for each question you ask, and your own code decides how high it must be before you act on it.
Coming soon
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