Coder Legion - Recent posts tagged satire

A Message From Our Founder: On the Winding Down of LaaSy™

Thu, 29 Oct 2026 14:06:00 +0000

It is with a heavy heart, and a considerably heavier wool inventory, that I announce LaaSy™ will cease operations effective immediately.

This is not the outcome we envisioned when we set out to democratize autonomous camelid infrastructure. We believed enterprises were ready for pasture-native computing. We believed the world needed Deterministic Spitting™. We believed, perhaps most fatally, that the market would recognize the existential risk of Unmanaged Wool Sprawl before it was too late.

We were right about the vision. We were wrong about the timeline.

A Brief Post-Mortem

In the interest of transparency, and at the request of our investors, we want to share an honest account of how we arrived here.

Q1. Strong grazing momentum. The seed round closed oversubscribed. The team expanded to forty-seven full-time shepherds and one part-time goat. Morale was high. The pastures were green.

Q2. Series A closed at eighteen million dollars. WolfGuard AI™ entered beta. Early telemetry was promising, though in retrospect we may have over-indexed on predator observability at the expense of, for example, whether the llamas were happy.

Q3. We shipped Retrieval-Augmented Rumination™ to general availability. Adoption was slower than projected. Several enterprise customers reported that their Autonomous Camelid Agents™ had begun ruminating so deeply that they stopped grazing entirely. We classified this as a feature. The market classified it differently.

Q4. The coyotes got in.

What We Learned

Every company failure contains lessons, and we owe it to the ecosystem to name ours plainly.

We learned that a Camelid Control Plane™ operating across cloud, edge, and pasture-native environments is significantly harder to maintain than it is to put on a slide.

We learned that Deterministic Spitting™ is, at a fundamental and possibly biological level, not deterministic.

We learned that "SOC 2 Grazing Certified" is not a certification that exists, a fact our auditors raised somewhat later in the process than we would have preferred.

And we learned that when you build an elite Coyote Red Team™ to continuously probe your pasture boundaries, the coyotes eventually stop being a red team.

On Our B-TAP Attribution Status

We also want to address recent speculation regarding LaaSy™'s standing with the Bureau of Token Attribution and Provenance.

As part of our commitment to responsible AI infrastructure, LaaSy™ maintained extensive observability across every Autonomous Camelid Agent™, Retrieval-Augmented Rumination™ request, predator detection event, and grazing decision.

This turned out to be expensive.

Following a voluntary review that we were strongly encouraged to consider mandatory, B-TAP determined that LaaSy™ had failed to attribute substantial Context Tax, Retrieval Tax, Prose Tax, and Observer's Tax across its operations.

We respectfully disagree with several aspects of the finding.

In particular, we continue to maintain that sending the complete Herd Knowledge Graph to every llama before each grazing decision was necessary for enterprise-grade contextual awareness. B-TAP has characterized this practice as "reckless context hydration."

Our attorneys have advised us that B-TAP has no ability to compel, fine, or otherwise reach us, and that we should therefore be significantly more relaxed about this than we are.

We can, however, confirm that a significant portion of our unattributed Observer's Tax resulted from telemetry systems installed to determine why our token costs were increasing.

Those telemetry systems increased our token costs.

We subsequently deployed additional agents to observe the telemetry systems.

This did not improve matters.

The finding also identified a substantial amount of Prose Tax associated with internal strategy documents. Management disputes B-TAP's determination that the phrase "pasture-native agentic transformation ecosystem" could have been replaced with "llamas."

LaaSy™ has been entered into the Public Register of Non-Attributed Systems. We are unable to confirm this, because no one has ever been able to open the Public Register of Non-Attributed Systems.

Our appeals agent is currently reviewing the 14,882-page framework and has requested additional context.

We have turned it off.

On the Series C

Many of you have asked about the Series C.

The Series C did not close.

We remain grateful to Sand Hill Pastures Capital, Andreessen Alpacowitz, and Sequoia Grazing Partners for their early belief in us. We understand and respect their decision to reallocate toward opportunities with clearer paths to revenue, stronger unit economics, fewer unresolved attribution findings, and fewer actual animals.

We note, without further comment, that The General Mills Artificial Intelligence Initiative has returned its attention to breakfast cereals.

Migration and Offboarding

We know many of you have workloads still grazing in production, and we are committed to a responsible transition.

Effective today, all herds will be released to open pasture. We recommend customers export their wool, hay, tribal herd knowledge, and spit metadata before the fences come down at end of quarter. Because you maintained complete ownership under our Local-First Camelid Architecture™, this data was always yours. This was, in the end, one of the few promises we kept entirely.

The Herd Knowledge Graph will remain available in read-only mode for ninety days, after which it will be, appropriately, put out to pasture.

A Personal Note

Building LaaSy™ has been the honor of my professional life.

To our shepherds, our engineers, our one part-time goat: thank you. To our customers who trusted us with their most critical grazing workloads: thank you, and we are sorry. To the coyotes: well played.

We set out to prove that camelid sovereignty mattered. I still believe it does. Perhaps the next company to attempt this will succeed where we could not, ideally with better fencing.

The pasture is quiet now. The wool remains un-sheared. And somewhere, a single part-time goat is updating its résumé.

We were told, at the very beginning, that none of this would be a problem.

No Prob-Llama™.

Information without provenance is just gossip.

Camelids without provenance are just fuzzy rumors.

And a startup without revenue is just a very expensive petting zoo.

Introducing B-TAP: Because Your AI Infrastructure Hasn't Attributed Its Fair Share

Thu, 15 Oct 2026 13:53:00 +0000

Context isn't free. Retrieval isn't free. Observability isn't free. And an international standards body would very much like to see your receipts.

For years, artificial intelligence companies have operated under a dangerous assumption: tokens are somebody else's problem. Engineering teams deploy increasingly complex agent architectures. Agents call other agents. Those agents retrieve documents. The documents are stuffed into context windows. Supervisors synthesize the results. Observability systems watch the supervisors, and other systems watch the observability systems.

At the end of the month, somebody gets a bill. Nobody knows why.

That ends today. We're pleased to introduce the Bureau of Token Attribution and Provenance, or B-TAP, the first bureau of The Vernholt Secretariat and the one some of you will insist on calling the Token IRS no matter how many times we correct you. Our mandate is voluntary but sweeping: to harmonize the reporting of token costs across every model, agent, retrieval pipeline, and suspiciously autonomous llama, everywhere, forever. The Secretariat notes that "first" implies others. The Secretariat has no further comment at this time.

B-TAP cannot make you do anything. We want to be transparent about that up front. What B-TAP can do is publish a framework, issue guidance, and maintain a register. You will come to fear the register.

You Have Been Selected for Voluntary Compliance

Consider a typical multi-agent AI workload. A user asks a relatively straightforward question. Your orchestration layer sends the request to three agents. One performs retrieval against a vector database. Another consults a knowledge graph. A third receives the entire conversation history because somebody checked a box six months ago and nobody remembers why.

Their outputs are passed to a supervisor. The supervisor receives 47,000 tokens of context, produces a 600-token answer, and returns HTTP 200. Success. Your dashboard is green. Your finance team is crying.

Traditional AI cost monitoring can tell you what you spent. The B-TAP framework recommends that you also disclose a more uncomfortable thing: why you spent it. That's where attribution begins.

Know Your Taxes

The B-TAP framework currently recognizes several major classes of token taxation. Reporting them is, we cannot stress this enough, entirely voluntary.

Context Tax is assessed when information must be carried through active model context. Every instruction, retrieved document, conversation turn, agent output, and piece of supporting material occupies finite context and incurs processing cost.

Retrieval Tax applies to finding information before it can be used. Searching, ranking, reranking, fetching, filtering, and preparing candidates are not free merely because they happen outside the model.

Prose Tax is assessed when information consumes more representation than its useful information content requires. Your 900-word architectural vision statement may, upon review, turn out to mean "use the smaller model first."

Ingestion Tax covers the work required to transform information into something useful later. Parsing, normalization, deduplication, classification, enrichment, embedding, and other write-side operations all have costs.

And then there is Observer's Tax. Observer's Tax is what happens when you instrument the system to understand why it is expensive, only to discover that the instrumentation is also expensive. The framework acknowledges this with regret.

Form BTAP-1040

Every participating AI system is encouraged to file an annual Token Attribution Return. Consider the following hypothetical filer:

Ken Alger
Reporting Year 2027

Reported Activity	Assessment
Tokens processed	1,499,203,847,116
Context Tax	$417.63
Retrieval Tax	$206.11
Prose Tax	$173.29
Ingestion Tax	$58.40
Total Attributed Token Tax	$782.06 ¹

¹ The itemized figures above sum to $855.43. The stated total is $782.06. The difference reflects the Context Carryforward Deduction, the full Schedule R retrieval exemption, and one figure B-TAP declined to explain. The framework notes that reconciliation of attributed line items to the assessed total is "outside the current scope of the provenance standard." Math, the reviewing officer added, is hard.

The result reduced an assessment that should have run into six figures down to the amount shown. The reviewing officer described it as "technically compliant and deeply upsetting." Everything on this return is permitted, including the part that does not add up. That is the entire problem.

Filing is requested annually by the 29th of February. The date was fixed at the framework's founding, when the official establishing it was, by all surviving accounts, looking at a leap-year calendar. The error was noticed. Correcting it, however, would require amending the founding charter, which would require establishing the provenance of the original charter, which has been referred to committee. The deadline therefore remains the 29th of February, and in three years out of four it does not arrive at all. Filers in those years are neither late nor on time. The framework considers this acceptable.

Non-filing carries no penalty, no interest, and no legal consequence of any kind. It carries something worse, which we will get to.

Yes, You May Take Deductions

The framework recognizes that not every token is frivolous. Reasonable and necessary context may qualify for the Context Carryforward Deduction, while retrieval operations demonstrably required to answer a user request may be reported on Schedule R.

Organizations operating multi-agent systems are encouraged to attach Schedule AGENT, identifying each agent, its responsibilities, and why seventeen agents were necessary to answer a question about resetting a password. "Agentic architecture" is not, by itself, an acceptable disclosure. Neither is "the framework generated it."

Keep Your Receipts

This is where things become slightly less ridiculous, and I want you to notice the exact moment it happens.

Suppose a retrieval agent costs $0.004 during a request. That tells us something. Now suppose that retrieval operation returns 20,000 tokens, all of which are hydrated into a supervisor's context. The supervisor subsequently costs another $0.009.

How much did retrieval really cost?

The direct answer is still $0.004, but that's no longer the interesting answer. The retrieval operation may also have caused downstream Context Tax. We now have two different accounting questions: where was the cost incurred, and what caused the cost to be incurred?

A conforming B-TAP attribution record might look something like this:

span_id: retrieval-104
direct_cost: $0.0040
primary_tax: RETRIEVAL
cause: vector_search
returned_tokens: 20000

downstream:
  span_id: supervisor-105
  tax: CONTEXT
  attributed_cost: $0.0021
  caused_by: retrieval-104
  attribution_method: proportional

We haven't charged the same $0.0021 twice. We're recording lineage. The supervisor incurred the Context Tax, while the retrieval operation contributed to causing it.

Your accountant may now begin sweating.

Attribution Is Subject to Review

There is another problem: how do we know retrieval-104 actually caused $0.0021 of the supervisor's cost?

Sometimes we can measure it. Run the same workload without that retrieval material. If the supervisor costs $0.006 without it and $0.009 with it, we have evidence supporting a roughly $0.003 downstream effect.

Other times, we don't have a counterfactual. We might allocate the supervisor's context cost proportionally according to the tokens contributed by each source. That's useful, but it isn't the same thing as measuring causation.

The framework therefore requests that filers disclose their attribution methodology:

attribution_method:
  - measured_delta
  - proportional
  - estimated
  - unknown

Yes, your attribution record now needs provenance. B-TAP takes no position on whether this was inevitable.

The Register

Here is the something worse.

B-TAP cannot fine you. It cannot audit you in any binding sense. It cannot send anyone to your door, a fact I will return to shortly for personal reasons. What it can do is enter non-conforming systems into the Public Register of Non-Attributed Systems, and it would like you to understand that the register is public.

Public, in the sense that it exists.

Accessing the register requires a B-TAP portal account. Creating a portal account requires a reference number. Reference numbers are issued by post, to a registered address in a member jurisdiction, which you must already hold in order to receive the number that would let you see whether you are on the list. The portal is available at all times except for scheduled maintenance, which runs daily from 00:00 to 23:59 CET.

No member of the public has ever successfully viewed the Public Register. Its deterrent power is therefore total. You cannot confirm you are on it. You cannot confirm you are not. You will simply know, in the quiet way one knows these things, that your context hydration was reckless and that somewhere in Vernholt, a record says so.

A small coalition of objectors has argued that a register no one can open cannot deter anyone. B-TAP notes that it cannot verify this claim, as the objectors cannot access the register in which their objection was filed.

A Notice, For Illustration

Filers occasionally receive correspondence like this. It is not enforceable. It is, in every other respect, extremely stressful.

NOTICE TT-742

Our review found that you reported $12,481 in Retrieval Tax during Reporting Year 2027.

Telemetry indicates that retrieved content subsequently generated approximately $31,204 in downstream Context Tax. Of that amount, $8,117 has been attributed using measured deltas, $17,903 using proportional allocation, and $5,184 using undocumented methodology.

Please provide supporting records for the undocumented assessment.

Additionally, approximately 14.8 million tokens appear to consist of unnecessarily verbose Markdown introductions. These tokens have been reclassified as Prose Tax.

Your system's registration status is under review.

Suddenly, "our AI bill increased this month" seems like a remarkably primitive observation.

You Probably Noticed the Joke Stopped Being a Joke a Few Sections Ago

There is no B-TAP. At least I hope there isn't by the time you read this. But somewhere back around the receipts, the bit quietly turned into an argument, and I did that on purpose.

Let me get the personal part out of the way, since it is also the truest part. I run a couple of small websites out of Oregon. If a body like B-TAP declared jurisdiction over "any system reachable from a member jurisdiction," I would be, this instant, in cheerful and total violation of a framework I have never read. And nothing would happen. No one is flying from Vernholt to Silverton to discuss my context hydration. The entire apparatus of consequence would consist of a paper reference number I would never receive for a register I could never open. That gap, between sweeping declared reach and the practical inability to reach one person in a small town, is the joke, and it is not really a joke.

Here is the other part that isn't invented. Context Tax, Retrieval Tax, and Prose Tax are not things I dreamed up to give an imaginary agency something to collect. I have been writing about them, unironically, as real costs in real systems for a while now. The joke just gave them a bureaucracy.

The accounting problem underneath all of it is genuine. AI cost dashboards tend naturally toward aggregation: tokens consumed, model cost, agent cost, request cost, latency, and tool usage. Those are useful operational measurements, but as AI systems become compositions of models, retrieval systems, tools, agents, memory layers, and observability infrastructure, knowing where money was spent isn't necessarily enough to understand why it was spent.

A $0.03 model call may have become expensive because an upstream retrieval operation returned too much information. An agent may be cheap by itself while producing verbose output that makes every downstream agent more expensive. A retrieval optimization may reduce Context Tax while increasing Retrieval Tax, while an observability system intended to diagnose those costs may itself impose Observer's Tax.

Optimizing one number can simply move the bill somewhere else. That's why I like the tax metaphor: taxes make costs visible as consequences of architectural decisions. Once those costs have lineage, we can stop asking only "How much did this run cost?" and start asking "What architectural decisions caused it to cost that much?"

The first is accounting. The second tells us what to fix.

A Final Notice

If B-TAP actually existed, I suspect most of us would fail its review. Not because our systems are necessarily wasteful, but because we frequently don't preserve enough evidence to explain why their costs occurred.

We have bills, traces, and token counts. What we don't always have are receipts connecting architectural decisions to their downstream consequences. Perhaps we don't need a Bureau of Token Attribution and Provenance after all. We just need better attribution.

Although if you are currently running seventeen agents to answer a password-reset question, you may want to start gathering your paperwork anyway.

The suspiciously autonomous llama has already filed. It itemized.

Information without provenance is just gossip.

Tokens without provenance are just an invoice.

Your Hiring Process Needs HTTP Status Codes

Wed, 26 Aug 2026 15:46:00 +0000

Because "we'll be in touch" is not an observable state.

I submitted a job application recently.

It was one of those applications where you actually put in the effort. I read the job description carefully, tailored the resume, wrote a cover letter specifically for the organization, and answered the optional questions rather than pretending they were optional.

Then I clicked Submit and got... nothing.

No confirmation email. No "we received your application." No indication that a candidate record had been created. Just a browser page telling me the submission had succeeded and the vague hope that somewhere, deep inside an applicant tracking system, my carefully assembled application had not been written directly to /dev/null.

As a developer, I find this troubling. Not because I expect an interview, or because I think every recruiter owes me personalized feedback. I just want a status code.

And I think that's a smaller ask than it sounds like, for a reason I'll come back to at the end: the states already exist. Somewhere in that ATS, my application is in one. The decision not to show me which one is a product decision, not a privacy constraint.

The Web Solved This Problem Decades Ago

When software sends a request to another system, we generally consider it useful for the receiving system to say what happened. Did it work? Is it still processing? Was the request malformed? Is the resource gone? Did something catch fire on the server?

HTTP gives us an entire vocabulary for this.

Hiring systems, meanwhile, have developed their own protocol:

POST /careers/applications

[no observable response]

This is sometimes followed, anywhere from three minutes to six months later, by:

After careful consideration...

Instead of inventing vague candidate statuses like "Under Consideration," perhaps hiring systems could adopt something developers already understand.

The 2xx Family: Success, Allegedly

`200 OK`

A human being has reviewed your application.

Nothing else is implied.

Honestly, this alone would be revolutionary.

`202 Accepted`

Your application has been received and accepted for processing.

This is the most important status code in the entire hiring protocol. The candidate does not need the hiring manager's notes or a walkthrough of the internal workflow. They need:

202 APPLICATION_ACCEPTED

Now we know the thing exists.

`204 No Content`

Your application was successfully received.

We have chosen not to acknowledge this in any way.

The 3xx Family: You Have Been Redirected

`302 Found`

We found an internal candidate.

Thanks for playing.

`304 Not Modified`

Your application has been "Under Review" for 47 days.

There has been no change since the last time you checked, or the 23 times before that. There will be no change the next time either. Please consider caching this response locally.

`410 Gone`

The position existed when you applied. It no longer exists. No additional information is available.

At least 410 would be useful. The current discovery mechanism is noticing that your bookmarked job posting has started redirecting to the careers homepage.

The 4xx Family: This One's On You

`401 Unauthorized`

You must create an account before applying.

Your password must contain at least 14 characters, uppercase and lowercase letters, a number, a symbol, and one ancient Sumerian glyph. It cannot match any password you have used since 1997.

You will then manually enter every field from the resume you just uploaded.

You will never use this account again.

`403 Forbidden`

You have the required experience and qualifications.

Unfortunately, you live 37 miles outside the geographic boundary within which we have determined this Zoom meeting can occur.

`404 Not Found`

Hiring manager not found. Recruiter not found. Job posting not found.

Nobody knows who owns this requisition.

`408 Request Timeout`

After seven weeks without communication, the candidate has accepted another position.

The hiring team will contact them tomorrow to schedule the second interview.

`409 Conflict`

The position requires 12 years of production experience with a technology introduced six years ago.

The conflict cannot be resolved.

`417 Expectation Failed`

You expected the phrase "we'll be in touch" to imply future communication.

It did not.

`422 Unprocessable Content`

Your experience is relevant, but your career path does not fit cleanly into the predefined boxes in our applicant tracking system.

Human intervention may be required.

Human intervention is unavailable.

`425 Too Early`

You applied 14 minutes after the job was posted.

LinkedIn reports 612 applicants.

We have questions too.

`451 Unavailable For Legal Reasons`

Your qualifications are not the issue.

The issue is a background check vendor, a non-compete of uncertain enforceability, or a sponsorship question nobody wants to be the one to ask about.

The 5xx Family: It Was Never You

`500 Internal Server Error`

Something has gone wrong internally. Your recruiter left, the headcount was frozen, the hiring manager changed, Finance reconsidered the budget, the organization restructured, or the position was posted by accident.

We will communicate all of these possibilities using the same message:

We have decided to move forward with other candidates.

`502 Bad Gateway`

The recruiter says they are waiting for the hiring manager.

The hiring manager says recruiting owns the next step.

Your request cannot be routed.

`503 Service Unavailable`

Your recruiter is no longer with the company.

Their calendar link remains active.

`504 Gateway Timeout`

"We expect to have a decision by Friday."

Friday has passed. The specification does not define which Friday was intended.

Candidates Don't Need Distributed Tracing

There's a serious point hiding under all of this. Hiring has an observability problem, and it's usually mistaken for a communication problem.

Companies understandably cannot expose everything happening inside a recruiting process. Candidate evaluations are private. Interview feedback may be sensitive. Hiring managers need room to compare people and make decisions.

That's fine. Nobody is asking for:

GET /hiring-manager/private-thoughts/about-me

But there is an enormous amount of territory between exposing confidential deliberations and providing no information at all.

A hiring pipeline already has states. An application was received. It entered review. Someone reviewed it. An interview was requested. The requisition was paused. The position was filled. The position was canceled. The candidate was declined.

Those state transitions already exist in the system. They are already recorded, timestamped, and reportable, because that's how recruiting teams measure their own funnel. The candidate is the one participant in the process who cannot see the record they're in.

Give Us the Boring Version

Imagine an applicant portal that reported nothing more than this:

202  APPLICATION_RECEIVED     Mar 04
200  REVIEWED                 Mar 19
304  NO_CHANGE                Apr 02
304  NO_CHANGE                Apr 30
410  POSITION_CLOSED          May 12

That's not radical transparency. It's barely transparency at all. But it tells you the system is functioning.

It removes the need to wonder whether an application disappeared. It reduces pointless portal refreshing. And it prevents candidates from reading silence as information, when silence might mean anything from "the hiring manager is on vacation" to "the requisition was canceled two weeks ago."

Mostly, it treats applicants like participants in a process rather than packets transmitted into an undocumented endpoint.

`200 OK`

I don't expect every application to result in an interview. I've submitted enough of them to have considerable empirical evidence supporting that position.

I don't expect detailed rejection feedback either. I understand why companies are reluctant to provide it. I don't even particularly mind 403 REQUIREMENTS_NOT_MET or 410 POSITION_FILLED. Those are answers.

What makes modern hiring uniquely frustrating isn't rejection. It's uncertainty about whether anything is happening at all.

Software engineers have spent decades building systems around a simple principle: when one system asks another to do something, the response should carry enough information to understand what happened.

Candidates aren't asking for distributed tracing of your recruiting infrastructure.

We'd settle for a status code.