steph france · agents in real companies
SKILLS
Knowledge compounding machines for your business.
why my agents keep getting better — and yours start from zero
the problem
Great work Tuesday.
Amnesia Wednesday.
Knowledge leaves in closed chats
Knowledge leaves with employees
Knowledge is rented from SaaS
every session starts from zero — the agent is smart, the company learns nothing
the mechanism
A skill is a file. Not a feature.
skills/platform-slack/
├── SKILL.md
├── CONTEXT.md
├── LEARNINGS.md
├── LOGS.md
├── references/
├── scripts/
└── tests/
plain Markdown, in a folder you own
the agent reads it when the task matches
open on camera — no black box
works with any model, survives every model
inside one real skill
Every part is just a file
- SKILL.md — the procedure, read when it triggers
- CONTEXT.md — local truth: identities, paths, boundaries
- LEARNINGS.md — gotchas from real runs · where it compounds
- LOGS.md — what ran, when, what happened
- references/ scripts/ tests/ — depth, code, proof
LIVE — walk the real platform-slack folder, scroll the LEARNINGS gotcha list
why it compounds
The compounding loop
do real work
→
capture it as a skill
→
next run reads it
→
run writes lessons back
⟲ every loop makes the next run better
the model never got smarter — the workspace did
my library, ~100 skills
Six kinds of skills
core-*
how every agent thinks: plan, build, research, review
platform-*
one external tool each: Shopify, Slack, Klaviyo…
tool-*
production methods: diagrams, video, ads
wf-*
scheduled workflows that run themselves
cd-*
commands: /save, /resume, /process
system-*
internal capabilities, agents maintaining agents
structure
Skills point to skills
TOOLS.md → "read platform-klaviyo first"
SKILL.md → loads references/ only when needed
big skills branch into small ones
progressive disclosure:
the agent reads only what the task needs
context stays small,
knowledge stays deep
auto-improvement
Skills that improve skills
Skill Forge
creates and audits skills
Workflow Forge
turns skills into scheduled jobs
Feedback rule
every correction updates the skill, not the chat
it took 6 failed versions of one skill to learn this — and that history lives in the file
why not just…
Skills vs the usual answers
| fine-tuning | slow, expensive, frozen at training time |
| one giant prompt | context bloat, no structure, no history |
| RAG alone | retrieves facts, not procedures or judgment |
| skills | owned files: procedure + context + lessons, versioned in git |
where good skills come from
The best skills don't come from Twitter.
They come from your company.
a downloaded skill knows the tool · your skill knows your business
LIVE — a skill born from one real conversation (founder process → skill file)
the warnings
External skills: last, not first
- use external skills when your own foundation is ready
- a skill is instructions your agent will obey — read before you install
- never let a skill smuggle credentials or hidden calls
- inspecting a source and obeying it are different acts
the carry-away
Your agent's intelligence lives in files you own — not in the model.
models will change again next year · your skill library survives all of them
start today: take the last useful thing your agent did — and make it a file.