Product Management¶

November 6, 2023
in AI Governance, Knowledge Strategy, Product Management
3 min read

GPTs turn prompting into configuration management

At its first developer conference, OpenAI has introduced generative pre-trained transformers (GPTs): custom versions of ChatGPT that can combine instructions, uploaded knowledge, and selected capabilities for a particular purpose. People can build them without conventional programming and share them inside an organization or, eventually, through a public store.

This will make useful experimentation easier. It will also turn a large number of informal prompts into organizational configurations that can affect real work.

July 11, 2023
in Human-Centered AI, Knowledge Strategy, Product Management
3 min read

Long context changes the knowledge-work interface

Anthropic has released Claude 2 with a context window that can accept roughly 100,000 tokens—enough for hundreds of pages of material in one prompt. The immediate attraction is obvious: a user can bring a long report, technical documentation, or even a book into a conversation without dividing it into tiny fragments.

More context changes what a language model can see. It does not guarantee that the model will attend to the right thing.

July 6, 2023
in Platform Engineering, AI Governance, Product Management
3 min read

Stable model access is part of the control plane

OpenAI has made the Generative Pre-trained Transformer 4 (GPT-4) application programming interface generally available to existing paying developers and announced a retirement path for several older completion and embedding models. The two developments belong together. Production access is not only about opening capacity; it is about managing change.

When an external model becomes part of an application, version stability and migration become product concerns.

June 27, 2023
in Product Management, AI Engineering, Human-Centered AI
3 min read

The AI product is more than the model

Microsoft has spent the spring adding generative artificial intelligence capabilities across Azure, developer tools, and business applications. In this month's platform update, one sentence deserves more attention than another feature list: generative AI does not absolve builders from thinking about what good product-making looks like.

That should be the operating principle for the current wave of experimentation.

June 13, 2023
in AI Security, Enterprise Architecture, Product Management
3 min read

Function calling moves risk beyond the chat window

OpenAI has added function-calling support to its chat models. Developers can describe functions using structured definitions, and the model can return arguments that an application may use to call external tools or retrieve information.

This is an important improvement for building reliable integrations. It also makes a boundary explicit: the model proposes; the application decides what happens next.

April 5, 2023
in AI Assurance, Product Management, Operating Models
3 min read

AI safety must travel with the product

OpenAI has described its approach to artificial intelligence safety, including pre-release testing, external input, human feedback, monitoring, and phased deployment. The account reflects an important reality: safety is not a property added once to a model and inherited automatically by everything built with it.

Safety has to travel with the product.

March 14, 2023
in AI Assurance, Risk Management, Product Management
3 min read

GPT-4 raises the standard for deployment evidence

OpenAI has released Generative Pre-trained Transformer 4 (GPT-4), a multimodal model that accepts image and text inputs and produces text. The accompanying technical report and system card describe strong performance across professional and academic benchmarks, alongside familiar limitations: unreliable facts, reasoning errors, bias, and behavior that can be difficult to characterize completely.

The release offers more than a new capability. It offers a useful distinction between evidence about a model and assurance about a deployed system.

February 16, 2023
in AI Governance, Human-Centered AI, Product Management
3 min read

Model behavior is an organizational decision

OpenAI has published a useful account of a difficult problem: how should a conversational artificial intelligence system behave, and who should decide? The company describes tensions among default behavior, user customization, safety boundaries, and the wide range of values held by people who use the system.

The question is often framed as model alignment. For organizations deploying these systems, it is also product governance. Every default encodes a decision about authority, acceptable variation, and whose judgment applies when values conflict.