How can AI actually help product managers and startup founders today?
AI is everywhere right now - from copilots and chat assistants to analytics, research, and planning tools. But beyond the hype, I’m curious about what’s truly useful in day-to-day product work.
From a PM or founder perspective:
Where has AI genuinely saved you time?
What tasks do you trust AI with - and what do you never delegate?
Has AI changed how you write specs, manage roadmaps, or talk to users?
What AI use cases sounded great in theory but failed in practice?
Personally, I see a lot of potential, but also a lot of noise. I believe that in the future, AI should help us much more. Create good roadmaps, convert product specs into concrete tasks, prioritise them, assign people, push for realisation, and much more.
Would love to hear concrete examples of how you’re using AI in real product and startup workflows 👇
Replies
Lookin' at your fourth bullet; one use case that sounded great in theory and is pretty trending within the funding ecosystems: AI will let anyone run a company solo.
In practice, it reduces the human capital-burden, but you still need a founder personality, taste, accountability and the willingness to push though ambiguity. This debates comes often with the claim "all these human-capital-intensive products 5 years ago could be easily turned into a lucrative side hustle nowadays". Imho, AI can compress execution but it doesn't replace conviction.
Dokably
@marces_wiliam well-said. But I still see that AI is still like a co-pilot in the execution sphere. But I am constantly trying new AI apps to test and understand the progress in the sphere.
I love the focus on 'beyond the hype'! I trust AI f.e. with competitor analysis and data synthesis, but I’d never delegate talking to users. There’s so much nuance in a live conversation that an agent just can't capture yet. AI is great for creating the 'bones' of a spec, but the 'soul' still has to come from us. Excited to see how these workflows evolve in 2026!
Dokably
@tereza_hurtova thanks for your feedback! totally agree that talking to people can't be delegated. Maybe in some surveys - yes.
TinyCommand
From a PM lens, AI has been most valuable in execution-heavy work. I use it extensively for writing product specs, breaking them into user stories, and generating test cases, and it takes roughly one-fifth of the time compared to doing this manually. It helps me move faster from intent to structured output without compromising clarity.
As a founder, we also use AI to automate operational workflows like lead generation and internal processes, where it compounds efficiency through automation rather than decision-making. One area I deliberately do not use AI for is talking to customers. At our current stage, understanding user intent, frustrations, and what they are actually trying to build requires direct human conversation, even if AI supports preparation through research or summarisation.
Dokably
@priyanka_gosai1 thanks for sharing! do you use any particular AI tool or chat GPT covers most of your needs? I am looking all the time for good AI tools especially for my product management work.
TinyCommand
@sasha_dikan ChatGPT. I have trained it on my product, we also use an extension of this for our support and so the model keeps learning with time. We get a lot of new feature queries from our support since we are quite early stage and so it also helps me generate a user story from those instantly.
I built a mobile app (SelfOS) with zero coding background using only AI - so here's my take:
Where AI saves time: Code generation, debugging, drafting marketing copy, brainstorming features.
What I don't delegate: Final product decisions, understanding user "why", design taste.
What failed: Vague prompts like "make it better" = vague results. And trusting AI code without understanding it leads to bugs you can't fix.
Biggest unlock: AI didn't replace thinking - it removed the "I can't code" barrier.