ON AIR SESSION 00:00 CHANNELS TUNED 0/4 LAST FULL SCAN

LISTENING POST / FIELD GUIDE FOR NEW OPERATORS

You don't need to know how it works.
You need to know how to ask.

Four short channels teach the actual mechanics behind AI coding — prompting, tools, agent loops, context — with live demos you can poke at. Below that, a running log of what's genuinely free to use right now, rechecked on a schedule so it doesn't go stale.

live signal — move your cursor over it

CH.1 PROMPTING

The model can't read your mind. It reads your words.

Most bad results trace back to a vague ask, not a weak model. Type a real prompt on the right and watch what gets flagged.

  • Name the concrete outcome, not the vibe
  • Give constraints: format, length, what to avoid
  • Show an example if the shape matters
TRY IT — nothing you type leaves this page
clarity score0/100
  • Start typing to get feedback.

CH.2 TOOLS & FUNCTION CALLING

This is how a model actually does things, not just talk.

You give the model a schema describing a function. It doesn't run the function — it decides when to call it, and hands back structured arguments for your code to execute.

  • The schema is a contract, not a suggestion
  • The model only ever returns arguments — your code runs the real thing
  • Results get fed back in before the model answers
SCHEMA GIVEN TO THE MODEL
{
  "name": "get_weather",
  "parameters": { "city": "string" }
}
USER"what's the weather in Lisbon right now?"
MODELcalls get_weather({ "city": "Lisbon" })
TOOL→ { "tempC": 24, "condition": "clear" }
MODEL"It's 24°C and clear in Lisbon."

CH.3 AGENTS & LOOPS

An agent is just this loop, run until the job's done.

Think, act, observe, repeat. No new magic over Channel 2 — just the same tool-calling step wired into a loop that keeps going until the task is finished or it gets stuck.

  • Each cycle re-reads the result before deciding the next move
  • Loops stop on success, a limit, or a human stepping in
  • This page's "what's new" log below is refreshed by exactly this kind of loop
PICK A TOY TASK
press play to start the loop…
cycle 0 of 2

CH.4 CONTEXT & MEMORY

The context window is a desk, not a filing cabinet.

Everything the model can "see" this turn — instructions, chat so far, open files — has to fit on the desk at once. Add files below and watch the desk fill up.

  • Once it's full, the oldest material gets summarized or dropped
  • That's why long sessions get compacted, not remembered word-for-word
  • Durable facts need to live outside the window — a memory file, not the chat
CONTEXT WINDOW — simulated, 20 "slots"
system prompt conversation open files

System prompt reserved. Add files or conversation to fill the window.

FREQUENCY LOG

What's actually free to use right now.

Curated, not exhaustive — a running log of free-tier and open AI coding capability, rechecked on a schedule by a research agent so this doesn't calcify into a 2026 relic.

Last full scan: · 0 entries tracked

SIMULATED CODER

Talk to a simulated coding assistant.

Scripted, not a live model — there's no API behind this, nothing you type leaves the page. But it's built to answer the way a careful one would: plain language for questions, and a visible think → act → observe trace when you ask it to actually fix or build something.

tip: press / anywhere on the page to jump here

OPERATOR LOG

Milestones, tracked locally.

Saved to this browser only. Nothing leaves your machine.

Tune at least one channel to generate one — it's a real image, rendered from your actual progress.