PRODUCTHEAD: What to consider when implementing AI in your product

these are my twisted products #

every PRODUCTHEAD edition is online for you to refer back to

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tl;dr

Implementing AI means assessing user needs and your data sources

AI technologies run the risk of creating harm — how are you planning for that?

LLMs and genAI open up new vectors for novel attacks that need to be countered

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hello

It was very kind of Janna Bastow and her team at ProdPad to include my book in their list of the 16 best product management books. She had also asked contributors to share their own favourites. I picked Erika Hall’s Just Enough Research (2024 ed.) and Steve Blank’s The Four Steps To The Epiphany.

You can read the full list of book recommendations from people such as Matt LeMay, Petra Wille, Roman Pichler and others over on the ProdPad blog.

(Disclosure: Product People is a ProdPad partner, but we didn’t give or receive anything in return for being included in the article.)

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The theme for this week’s PRODUCTHEAD broadly centres on how to actually go about adding some kind of AI-related tech to the products and services you provide. I appreciate that many organisations have already dived straight in and are picking their own way around the various pitfalls. Nevertheless, you may find the content this week catches aspects you may have not yet considered.

While the thought of your country’s government plastering AI over everything may not fill everyone with confidence, the technical guidance on GOV.UK is generally written in plain language by people who know their subject. While companies may not have the equivalents of ‘policy teams’, it isn’t that hard to tweak the guidance offered for use in a commercial setting, particularly when it comes to the ethics advice later on.

Similarly, as a few trailblazers have already found out to their detriment, a prompt-based interface is a new vector for novel attacks. Despite the safeguards you or the supplier may have engineered in, large language models (LLMs) remain naive and susceptible. The article I’ve included from promptfoo is a useful explanation of the kinds of threats you need to counter in your product design.

Speak to you soon,

Jock

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what to think about this week

Planning and preparing for artificial intelligence implementation

Once you have assessed whether AI can help your team meet your users’ needs, this guidance will explore the steps you should take to plan and prepare before implementing AI.

Applying discovery, alpha, beta phases to AI tech

[GOV.UK]

Launching the Artificial Intelligence Playbook for the UK government

To meet the needs of a wide and diverse audience, the AI Playbook includes accessible explanations on AI technologies, sample use cases, and corporate guidance for policy professionals and decision makers, as well as technical advice on how to buy, implement and use AI solutions for digital and data professionals.

A starting point for the uninitiated

[Tommaso Spinelli / Government Digital Service]

RAG data poisoning: key concepts explained

AI systems are under attack – and this time, it’s their knowledge base that’s being targeted. A new security threat called data poisoning lets attackers manipulate AI responses by corrupting the very documents these systems rely on for accurate information.

Understand the new attack vectors opened by genAI

[promptfoo]

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recent posts

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AI is neither a panacea nor a magic bullet just as digital wasn’t for UK gov

[I Manage Products]

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We cover topics including:

» Should you hire freelancers in your product team?

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+ more :-)

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For this article, I’ve focused specifically on the ‘coding in the open’ part. I’ll cover how it benefits public sector organisations, and how — in the right circumstances — it can yield a strategic advantage to commercial organisations also.

Increased scrutiny keeps us all a bit more honest

[I Manage Products]

PRODUCTHEAD is a newsletter for product people of all varieties, and is lovingly crafted from ethernet cables.