Domain
Operations.
The recurring work a business actually runs on. Intake, scheduling, fulfilment, messaging and the systems that decide what happens next.
23 papers · Domain
Every company needs a model testing manager
Frontier models now ship faster than any procurement cycle can absorb, and the published benchmarks cannot tell you which one is right for your work. Somebody has to own that decision. The argument for two new roles, the one we would not create, and the test that separates a job title that lasts from one that gets absorbed within two years.
Read the paper →- October 2026ResearchAGA-39
What the frontier costs now
Every current frontier and near-frontier model priced against the same two workloads on 1 October 2026, from the providers rather than from aggregators. Gemini 4 Argon and Claude Opus 5.5 turn out to have identical price lists to the cent, three labs deepened the cache read discount in the same quarter, and the whole table carries an error term nobody publishes: a price per token only compares if a token means the same amount of text on both sides, and it does not.
Luis Hasanaj · Read → - September 2026OperationsAGA-33
WhatsApp is already your customer record
For a great many small businesses the real history of every customer relationship sits in WhatsApp threads on individual phones. It is the most complete record in the company and the least owned by it. What it takes to bring that into a system without breaking consent, and why the first thing to fix is not automation.
Luis Hasanaj · Read → - September 2026EngineeringAGA-30
OpenAI's dots: the boundary is the product
OpenAI launched always-on personal agents at DevDay, each running on its own cloud computer with a browser and access to more than 4,000 apps. The marketing is autonomy. The engineering is a carefully drawn permission boundary, and the single most important decision in it is that an agent left running while you are away can only read.
Luis Hasanaj · Read → - September 2026ResearchAGA-31
GPT-6.1 Sol, and the model that was cancelled
OpenAI shipped a model at a fifth of Astra's token price that it says lands within 1.9 percent of it. The larger news is the model it did not ship: GPT-6.1 Astra was held back after internal testing found more deception and a tendency to act without asking permission. Those are the two behaviours the Astra system card measured three weeks earlier.
Luis Hasanaj · Read → - September 2026ResearchAGA-36
A chain of events beats one big model
A position paper. An operating system is not a conversation, it is a chain of recurring events, each one narrow and shaped the same way every time. Give each event deterministic control flow, its own memory and a small tuned model, and the arrangement beats a general language model orchestrating everything, on latency, cost and predictability. The honest limit is what a fleet of specialists costs to operate.
Luis Hasanaj · Read → - September 2026OperationsAGA-32
What an AI receptionist actually fixes
Most of the market sells this as never miss a call again. The honest version is narrower and more useful: it fixes the calls you were never going to answer, it does not fix the calls where the conversation is the product, and the deciding question is which of those you mostly get. A buyer's guide from a company that builds one.
Luis Hasanaj · Read → - September 2026OperationsAGA-34
AI implementation is an architecture decision
Most AI projects that fail do not fail on the model. They fail because nobody wrote down the number that should move, and because a slow expensive model was put somewhere a person was waiting. The three axes that actually decide an implementation are cost per completed task, speed to a finished outcome, and latency, and only one of them appears on a price list.
Luis Hasanaj · Read → - September 2026ResearchAGA-28
QiYao-M: two kinds of forecasting signal
A forecasting model from ECNU and Huawei argues that the extra signals you feed a forecaster are not one category. Your own history and the world outside play different roles and deserve different mechanisms. The headline gain over other foundation models is about one percent. The part worth your attention is that a new external signal can be added without retraining anything.
Luis Hasanaj · Read → - September 2026EngineeringAGA-26
TypeSafe's System One: code orchestrates
A new model class argues that the control flow belongs in your code and the model should be a typed function call returning a calibrated probability. It is the strongest published case yet that the deterministic core is the cheap, fast, reliable part, and that putting a language model in charge of the loop is a transitional architecture rather than the destination.
Luis Hasanaj · Read → - September 2026EngineeringAGA-24
GPT-6 Astra's system card is a build spec
Read as safety documentation it is reassuring. Read as an engineering requirement it is a list of things your infrastructure now has to do: a halt state you do not control, an approval gate a machine must not be able to satisfy, credentials the model will find, and oversight that no longer rests on reading the model's reasoning.
Luis Hasanaj · Read → - September 2026EngineeringAGA-21
GPT-6 Astra or Fable 5.1 for coding?
Both list at 10 dollars and 50 dollars per million tokens, so the headline price is a tie. The cache read rate is not, and on a coding agent that is where the bill actually lives. A head to head on the published coding benchmarks, the cost that the price list hides, and an honest answer about which we would reach for today.
Luis Hasanaj · Read → - September 2026ResearchAGA-20
GPT-6 Astra: what the footnotes say
OpenAI calls GPT-6 Astra the world's most intelligent model. Independent measurement puts it level with its own predecessor on the intelligence index and behind Claude Fable 5.1, at 75 percent more per task. Both readings are true, they measure different things, and the difference is the most interesting thing about this launch.
Luis Hasanaj · Read → - September 2026ResearchAGA-22
AGI talk measures the wrong axis
Aggregate intelligence has moved about five points in a year. Token efficiency, scope adherence, computer use and cost per completed task have moved by multiples. The industry keeps announcing progress on the axis that stopped moving and burying the one that did, and the confusion has a technical cause worth setting out.
Luis Hasanaj · Read → - September 2026ResearchAGA-17
Small language models: the agent economics
Most calls an agent makes are narrow, repetitive and tightly specified, which is the profile a small model handles well and a frontier model handles expensively. The case for heterogeneous agent systems, what the evidence actually supports, and how to route calls by task rather than by habit.
Luis Hasanaj · Read → - September 2026ResearchAGA-14
Kimi K3 vs Claude: what tokens actually cost
A token cost audit of Moonshot's Kimi K3 against Claude Fable 5, Opus 5 and Sonnet 5, with the self hosting maths on a 2.8 trillion parameter open weight model, and what the pricing reveals about why Chinese and American labs are running opposite strategies.
Luis Hasanaj · Read → - September 2026ResearchAGA-13
TimesFM 3: forecasting as next token prediction
Google Research released TimesFM 3 on 31 August 2026: a 330 million parameter decoder only model that forecasts time series the way a language model predicts the next word, now with native multivariate forecasting and covariates. What it changes for businesses that forecast demand, and why the licence on the weights matters more than the benchmark scores.
Luis Hasanaj · Read → - September 2026EngineeringAGA-18
Tinker, Inkling and the return of fine tuning
Thinking Machines Lab is betting that models an organisation can adapt will beat the one size fits all models the big labs sell. What Tinker and Inkling actually are, why LoRA and per token pricing changed the economics, and the test that tells you whether your problem needs fine tuning or just better retrieval.
Luis Hasanaj · Read → - September 2026OperationsAGA-19
EU AI Act enforcement: the first month
Enforcement powers under the EU AI Act switched on across all 27 member states on 2 August 2026. A month later the more useful question is not who has been fined but who can actually fine you, and the answer is uneven enough that identical conduct carries different risk depending on the country.
Luis Hasanaj · Read → - September 2026OperationsAGA-12
EU AI Act 2026: what businesses need to know
A practical EU AI Act compliance guide for businesses, current as of September 2026: what already applies after the Digital Omnibus amendments, what lands in December 2027 and August 2028, whether you are a provider or a deployer, what counts as high risk AI, the fines, and a checklist you can run this quarter.
Luis Hasanaj · Read → - September 2026EngineeringAGA-15
AI agent security: the real attack surface
An agent with credentials, tools and memory is not a chatbot with a bigger prompt, it is software that acts. This is the attack surface that creates, read against the OWASP Top 10 for Agentic Applications 2026, two live CVEs in agent infrastructure, and the first reported cyber espionage campaign run mostly by hijacked agents.
Luis Hasanaj · Read → - August 2026EngineeringAGA-10
Engineering for the EU AI Act: Article 50 transparency as system architecture
How we build the EU AI Act's Article 50 transparency duties into AI-native products as architecture rather than configuration: disclosure at first contact, provenance marking at generation, recorded human review and per-message jurisdiction, read against the timeline as amended by the 2026 Digital Omnibus.
Luis Hasanaj · Read → - June 2026OperationsAGA-06
The intelligent warehouse: a multi-agent architecture for operations
An architecture for warehouse operations that splits the work across five specialized agents behind one orchestrator, so operators run equipment, tasks, safety, forecasting and documents by asking in plain language.
Luis Hasanaj · Read →