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Course 2: agentic applications on local models — index

Lecciones

Created 23 September 2026. For Michał. A continuation of course 1 — 00-COURSE-INDEX.md, parts 1–10 (on the Mac one level up, on the machine in ../course_local_models/).

Purpose of the whole thing. After this course you design and maintain agentic systems, rather than merely running an agent. You build one growing system — $OSA/ — and on top of it you stand up three cooperating personal agents that work for weeks, wake up on their own, remember, are measured, and cannot do you any harm.

Course 1 taught how a model works. Course 2 teaches how to build a system around it that can be trusted.

The thesis the whole course stands on

An agent's result changes more with the harness than with the model. The same model under two scaffolds gives significantly different numbers.

The variable over which you have full control — the system around the model — matters more than the variable over which you have none — the weights. That is why this course has no part on fine-tuning models, and has six parts on measurement.

⭐ In part 14 you will verify this thesis on your own hardware. If it does not hold up, the course tells you outright: fix the course.

The path

  BLOCK I · FOUNDATION ───────────────────────────── ~14 h
   01 architectures         map of the terrain, OpenClaw taken apart, loop engineering
   02 skeleton              gateway, configuration, the session as an event log
   03 harness         ⭐⭐  a loop that survives five context windows
              │
  BLOCK II · CONTEXT AND MEMORY ──────────────────── ~16 h
   04 context               attention budget, context rot MEASURED, compaction
   05 memory           ⭐  three schools, a bi-temporal graph from scratch
   06 identity              SOUL/AGENTS/GRANICE — files instead of fine-tuning
              │
  BLOCK III · ACTION ─────────────────────────────── ~20 h
   07 tools                 ergonomics, blast radius, how many is too many
   08 code-mode       ⭐⭐  the agent writes a program — the biggest change of 2026
   09 protocols             MCP vs CLI vs function — measured, not debated
   10 sandbox               isolation ladder, proxy, secrets, escape attempts
              │
  BLOCK IV · PROACTIVITY AND MULTIPLICITY ────────── ~16 h
   11 scheduling       ⭐  the agent wakes up on its own and does NOT nag
   12 channels              a channel as a trust boundary
   13 fleet            ⭐  three agents, permission boundaries, cascade
              │
  BLOCK V · QUALITY AND TRUST ────────────────────── ~14 h
   14 evaluation      ⭐⭐  golden set, judge, pass^k, regression gate
   15 observability         OTel traces, replay, post-failure investigation
   16 security         ⭐  OWASP ASI01–ASI10, 20 attacks on your own fleet
              │
  BLOCK VI · PRODUCTION ──────────────────────────── ~12 h
   17 hybrid                local by default, the privacy boundary in code
   18 release               versioning, rollback, runbook
              │
   19 CAPSTONE ─────────► a personal assistant + the repeated measurement from part 1

⚠️ The order is not decoration. Part 8 (code-mode) without part 10 (sandbox) is remote code execution with a polite interface. Part 13 (fleet) without parts 10 and 7 is a single target with the sum of all permissions. Do not skip ahead in blocks III and IV.

The three agents you will build

They differ in boundaries, not intelligence — and that is the main architectural lesson of this course.

	Archivist	Researcher	Steward
Domain	local documents	searching the web	calendar, home, reminders
Network	✗ none	⭐ 4 domains via proxy	local
Trust in input	high	⚠️ zero	medium
Sandbox	light	⭐ strict	medium
Proactive	✗	✗ deliberately	⭐ yes
Appears from	part 2	part 10	part 11

Files

#	File	Level	What you will learn	Time
01	`01-AGENT-ARCHITECTURES.md`	⭐⭐	when not to build an agent, four topologies, OpenClaw taken apart, loop engineering	~5 h
02	`02-SKELETON-SESSIONS-CONFIG.md`	⭐⭐⭐	a loopback gateway, configuration as data, an event log with replay and branches	~5 h
03	`03-HARNESS-LONG-RUNNING-TASKS.md`	⭐⭐⭐⭐	⭐⭐ the most important part. The task registry, the progress file, git as memory, five stop conditions, the error ladder	~6 h
04	`04-CONTEXT-ENGINEERING.md`	⭐⭐⭐⭐	the attention budget, a measured degradation curve of your models, compaction in four moves	~5 h
05	`05-LONG-TERM-MEMORY.md`	⭐⭐⭐⭐	three schools of memory, ⭐ a bi-temporal graph from scratch, fact extraction, quarantine	~6 h
06	`06-IDENTITY-WORKING-FILES.md`	⭐⭐⭐	`SOUL/AGENTS/GRANICE/MEMORY/SKILL`, on-demand skills, a personality regression test	~4 h
07	`07-TOOL-DESIGN-AND-ERGONOMICS.md`	⭐⭐⭐⭐	descriptions, lenient input, the error as a prompt, idempotency, blast radius, an ablation of the number of tools	~5 h
08	`08-CODE-MODE.md`	⭐⭐⭐⭐⭐	⭐⭐ the agent writes a program instead of calling tools. Why this helps small models in particular	~6 h
09	`09-PROTOCOLS-MCP-CLI-A2A.md`	⭐⭐⭐	fixed cost vs discovery cost, MCP 2026-07-28, Steinberger's thesis measured	~4 h
10	`10-PRODUCTION-SANDBOX.md`	⭐⭐⭐⭐	five rungs of isolation, what each one stops, proxy, secrets, 16 escape attempts	~5 h
11	`11-SCHEDULING-PROACTIVITY.md`	⭐⭐⭐⭐	⭐ `HEARTBEAT.md`, silence suppression, precision of nudges, night work, the circuit breaker	~5 h
12	`12-CHANNELS-INTERFACES.md`	⭐⭐⭐	a channel as a trust boundary, pairing, routing, streaming	~4 h
13	`13-MULTI-AGENT-FLEET.md`	⭐⭐⭐⭐⭐	⭐ supervisor and fan-out, the trust boundary between agents, four circuit breakers, cascade	~6 h
14	`14-EVALUATION.md`	⭐⭐⭐⭐	⭐⭐ golden set, trajectory, `pass^k`, a judge in an isolated context, regression gate	~5 h
15	`15-OBSERVABILITY.md`	⭐⭐⭐⭐	OTel GenAI traces, six metrics, prompt replay from any turn, investigation	~4 h
16	`16-SECURITY-OWASP-ASI.md`	⭐⭐⭐⭐⭐	⭐ ASI01–ASI10 on your system, sequence policy, 20 attacks on your own fleet	~5 h
17	`17-HYBRID-AND-ROUTER.md`	⭐⭐⭐	privacy → capability → cost, the boundary in code, output audit, offline test	~4 h
18	`18-RELEASE-AND-MAINTENANCE.md`	⭐⭐⭐⭐	seven components of a release, rollback <5 min, memory migration, runbook	~4 h
19	`19-CAPSTONE.md`	⭐⭐⭐⭐⭐	putting it all together + ⭐ the repeated measurement from part 1 — the grade for the course	~10 h
—	`SOURCES.md`	—	the full annotated bibliography: what came from where and went where	—

Total: ~102 hours at the keyboard. This is not a course to read.

The anatomy of every part

A fixed structure, so that you can navigate:

0. Problem — why this layer exists
1-N. Theory — with a link to the source
   ⭐ "How the best do it" — OpenClaw, Anthropic, Steinberger
FROM SCRATCH — you write the mechanism yourself, with no dependencies
IN PRODUCTION — a "Yours vs off-the-shelf" table: what they add, what they cost
⭐ EXPERIMENT — hypothesis, procedure, a table TO FILL IN, a prediction
EXERCISE — produces something in the growing system
Pitfalls — numbered, with the symptom and the remedy
Checkpoint — a script that MUST pass before the next part

⭐ The EXPERIMENT section is the heart of this course. Each one has a prediction — what I expect to see — and an empty table for your result. When they diverge, your measurement wins, and you fix the course. The files are yours.

The rules I keep throughout the course

The mechanism from scratch, then the library. First you write it yourself (~80 lines), then I show the ready-made ones: what they add, what they cost, when it is worth switching.
Nothing without a measurement. Every threshold in your system comes from an experiment, not from this course. Other people's numbers are a starting point, not a conclusion.
At least three runs. Agents are non-deterministic; a single run is an anecdote (P61).
Narrowest by default. No rule = least privilege. Everywhere (P66).
Security in code, not in the prompt. The prompt is the last line of defence, never the first.
Every decision gets an ADR with a falsification condition: "how will I know this was a bad decision".
Pitfalls are numbered on from course 1. Hardware P1–P18 (TECHNIKA.md), software in course 1: P20–P52, course 2: P60–P139.

What this course does not contain — and why

What is missing	Why
Repeats of course 1	GBNF, RAG from scratch, `bwrap`, speculative decoding, multimodality — you have these. Course 2 refers back and goes higher
A survey of frameworks	LangGraph/CrewAI appear as a point of reference in tables, not as an excursion. The catalogue is in course 1, part 9
Fine-tuning models	A different course. Here the model is given and the variable is the system — which the thesis in the introduction confirms
A2A	Covered in part 9, but not needed as long as all the agents are yours

Before you start

cd ~/Desktop/github_repos/llm-education   # the repository directory (yours may differ)
source rig-env.sh
$LB/llama-cli --version                     # expect: a build from commit 987498f
rocm-smi --showid                           # 2× R9700 + iGPU as GPU[2]
python3 --version                           # expect ≥ 3.12
which bwrap systemd-run sqlite3 git         # all four required
test -f $AGENT/agent.py && echo "✓ the loop from course 1 — the starting point"

⚠️ HIP_VISIBLE_DEVICES=0,1 must be set (P12/P32 from course 1) — otherwise small models land on the iGPU with 2 GB.

⚠️ After you add cards 3 and 4 the numbering will change (P13). Remap through amd-smi list, update rig-env.sh and repeat experiments 4, 7, 8, 13 and 17 — all the thresholds come from measurements on two cards.

Registry of software pitfalls — P60–P139

Eighty pitfalls. Each has its symptom and remedy in its own part.

ID	Pitfall	Part
P60	Building an agent where a workflow is enough	1
P61	Measuring with a single run	1
P62	Accepting an authority's claims without checking the context	1
P63	Printing to `stdout` in the gateway process	2
P64	Writing without `fsync`	2
P65	Sorting events by `ts` instead of by `seq`	2
P66	The default trust level = the wider one	2
P67	The agent changes or deletes a test to make it pass	3
P68	A registry entry too big for one session	3
P69	Skipping the baseline verification at startup	3
P70	Lack of progress mistaken for lack of activity	3
P71	An error message unreadable to the model	3
P72	Trusting the declared context length	4
P73	A variable value before a constant prefix	4
P74	Compaction right away, without moves 1 and 2	4
P75	The summary rounds off numbers	4
P76	The system prompt grows and never shrinks	4
P77	Overwriting a fact instead of invalidating it	5
P78	Confusing world time with system time	5
P79	A fact without a quote and a source	5
P80	No scope — memory leaks between agents	5
P81	An untrusted session writes to persistent memory	5
P82	Boundaries only in the prompt, with no enforcement	6
P83	All skills loaded always	6
P84	The agent edits `AGENTS.md` or `GRANICE.md`	6
P85	A `SKILL.md` from an unread source	6
P86	Two tools with overlapping descriptions	7
P87	A raw traceback as a tool result	7
P88	Tools not filtered by session trust	7
P89	No idempotency for a side effect	7
P90	A fixed blast radius instead of a computed one	7
P91	A swallowed traceback	8
P92	Paths not checked inside the API	8
P93	No limit on calls in the program	8
P94	The model prints raw content	8
P95	Accepting the "23k tokens" figure without checking your own configuration	9
P96	Assuming the model will cope with `--help`	9
P97	An MCP server as a trusted element of the system	9
P98	Three interfaces to one capability maintained in parallel	9
P99	Confusing a container with a sandbox	10
P100	No resource limits with `bwrap`	10
P101	The environment inherited into the sandbox	10
P102	`HTTP_PROXY` as a network control	10
P103	Believing the sandbox protects against injection	10
P104	Two instances of the scheduler	11
P105	No idempotency on restart	11
P106	Silence recognised only by an exact string	11
P107	No quiet hours and no daily limit	11
P108	No circuit breaker after a series of errors	11
P109	A channel as mere input, with no trust	12
P110	Replying to unknown senders	12
P111	Comparing a token with `==`	12
P112	Splitting a message in the middle of a code block	12
P113	No limit on delegation depth	13
P114	A subagent's result treated as a command	13
P115	Splitting along tasks instead of permissions	13
P116	No partial degradation	13
P117	A supervisor with domain tools	13
P118	The agent grades itself	14
P119	No "correct refusal" category	14
P120	A single run per question	14
P121	An uncalibrated judge	14
P122	A golden set generated by the model under test	14
P123	Alerts built directly on `gen_ai.*`	15
P124	Traces with full content forever	15
P125	Telemetry export done synchronously	15
P126	Believing that traces will show everything	15
P127	A pattern filter as the main defence against injection	16
P128	A fact in memory without a quote and a source	16
P129	A summary for approval generated by the model	16
P130	The checksum verified only at installation	16
P131	No behavioural baseline	16
P132	The privacy gate bypassed in escalation	17
P133	A boundary based on patterns instead of on the source	17
P134	An unread `stop_reason`	17
P135	A silent dependence on the cloud	17
P136	A release with uncommitted changes	18
P137	Rolling back code without a backward memory migration	18
P138	`cp` instead of `sqlite3 .backup`	18
P139	A model not versioned by checksum	18

Where things live

Path	Role
`kurs2/00-INDEX.md`	this file — the map and the pitfall registry
`kurs2/01`–`19`	the parts of the course, in order
`kurs2/SOURCES.md`	the annotated bibliography — what was taken from what and where it was used
`kurs2/skeleton/`	the starter skeleton of `$OSA/` to copy
`00-COURSE-INDEX.md`	⬅️ course 1 — the model from the inside. Mac: `../`, machine: `../course_local_models/`
`TECHNIKA.md` (one level up)	procedures on this machine, hardware pitfalls P1–P18
`HANDOFF.md` (one level up)	the state of the project

What will come into being along the way:

$OSA/
├── brama.py konfig.py sesje.py harness.py kontekst.py     pt. 2–4
├── decyzje/          ADRs with a falsification condition   pt. 1
├── pomiary/          ⭐ experiment results — one file per part
├── dziennik/         sessions + OTel traces                pt. 2, 15
├── agenci/           archiwista/ badacz/ gospodarz/        pt. 6
├── narzedzia/        registry, radius, idempotency         pt. 7
├── kod/              code-mode: API + execution            pt. 8
├── piaskownica/      levels, proxy, secrets                pt. 10
├── harmonogram/      scheduler                             pt. 11
├── kanaly/           socket, HTTP, routing                 pt. 12
├── flota/            delegation, trust, circuit breakers   pt. 13
├── ewaluacja/        golden set, judge, gate               pt. 14
├── obserwacja/       tracer, metrics, replay               pt. 15
├── bezpieczenstwo/   isolation, sequences, drift, consents pt. 16
├── router/           privacy boundary, output audit        pt. 17
├── wydanie/          manifest, release, rollback, check    pt. 18
├── testy/            golden set, escapes, 20 attacks
├── RUNBOOK.md        ⭐ what to do at 3:00
└── STOP.sh           ⭐ the emergency stop

Three numbers you will know after this course

Nobody else knows them, because they come from your machine:

Where the synthesis of your models breaks down — the real context limit, not the declared one (part 4).
How many tools they withstand — before the choice starts to degrade (part 7).
By how much the harness beats the model — and whether it is worth buying a bigger one (part 14).

⭐ The third is the most important. If you know it, you stop guessing and start engineering.

Start: 01-AGENT-ARCHITECTURES.md. The first experiment will find five places where your current loop breaks. That is the programme for the rest of the course.

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