The fine-tuning vs RAG question usually arrives as a statement: “we need to fine-tune a model on our data.” It is one of the most expensive sentences in enterprise AI, and it is usually wrong. Not always, but usually. The request nearly always means one of two things: the model does not know about our business, or the...
API Development
Articles, guides and tutorials on building and consuming APIs, covering REST, GraphQL, API design principles and developer best practices.
The case for moving off OpenAI got considerably stronger during 2026. Open-weight models reached a level where the quality gap on ordinary production work became narrow, published pricing undercut the frontier providers, and the weights themselves became downloadable, which turns a supplier relationship into an option....
Most teams treat API security as an authentication problem. They add tokens, check them on every route, and consider the job done. Then a tester changes one number in a URL and reads another customer’s invoice. That gap between “authenticated” and “authorised” is where the majority of real API breaches live, and it is...
The Kimi K3 API arrived with an unusual combination behind it: frontier-adjacent benchmark results, aggressive pricing, and downloadable weights. Moonshot AI published those weights on 27 July 2026, which makes K3 the largest openly available model released so far and the first time a model at this scale has been...
Anyone estimating custom API development cost from the number of endpoints is going to be wrong, usually by a factor of three. Endpoints are the cheapest part. A dozen of them, reading and writing data you already hold, is a fortnight’s work for a competent backend developer. What costs money is everything that turns...
CRM and ERP integration is almost always described as a connection problem, and it is almost never a connection problem. Both systems have documented interfaces. Both have connectors available. The difficulty is that sales and finance have spent years describing the same business in two different vocabularies, and the...
Third-party API integration is the most consistently underestimated work in commercial software. The documentation reads clearly, the vendor publishes a client library, and someone says two weeks. Six weeks later the team is still arguing about what should happen when a webhook arrives twice for an order that was...
An OpenAI API integration looks trivial in a prototype and turns out to be an engineering project in production. The proof of concept takes an afternoon: install the client library, paste a key, send a prompt, get a useful answer back. Then someone asks what happens when the request times out, who pays when a customer...
Determining the true AI integration cost is a major financial step for UK businesses looking to deploy Large Language Models (LLMs) in 2026. Integrating AI into software applications automates customer service pipelines, increases productivity, and unlocks conversational data insights. However, budgeting for these...
Reducing LLM latency is one of the most critical challenges for engineers building responsive AI applications. While Large Language Models (LLMs) keep growing in capability, their token-by-token generation can create frustrating bottlenecks for end users, and long wait times lead directly to lower engagement and...