... entire result set to the browser and let it sort itself out. Same deal for Spanner. A lot of Basedash is just "run the SQL the user wrote, show the rows." We support 10+ dialects (Postgres, MySQL, BigQuery, Snowflake, Athena, SQL Server, Spanner, and friends), and every query gets paginated because we can't stream a 12M row result set to a browser. For years the approach was wrap-and-pray. Take whatever the user wrote, stuff ... ... have to understand its grammar to paginate it, which is exactly why it shipped fast and lasted years. It works great on the easy dialects but falls apart on the annoying ones. SQL Server has no LIMIT at all. Athena

... reactive. That world is gone. The real shift isn t that AI improves discovery -it s that it exposes how much of discovery today is still fragmented, episodic, and disconnected from actual decisions. That s why we built Athena -not to add AI to discovery, but to move toward a model where discovery is continuous, adaptive, and directly tied to what teams actually do next. Let s chat in the comments - how do you make sure you're building value ... ... anyone actually felt a meaningful change in the products themselves? It doesn't really seem that way. Comment from Tal Elor(@tal_elor): @andrew_king10  I agree. I would add that it is not only real-time vs

... uncomfortable truth is most roadmaps are built on assumptions dressed up as strategy. What changed things for us was talking to buyers before committing to build, not after. Simple, but almost nobody actually does it consistently. How does Athena help close that gap between what teams assume and what's actually validated? Comment from Jim Jeffers(@jim_jeffers): I d separate did users try it? from did it change the next decision they made? A feature can get curiosity clicks ... ... product value data is the only way teams can confidently embrace true flexibility. Comment from Maya Elor(@maya_elor): @nausad_alam  Great question, we measure it by automatically connecting product analytics data directly to specific business outcomes within Athena

... assess effort. But most evaluations happen with: Limited data No real validation Weak assumptions In a world where we can simulate and analyze more - why are we still relying on guesswork? This is the core problem Athena is trying to solve - bringing structured evaluation into early-stage decisions, not just post-launch analysis. Comment from Richard Smith(@richard_smith_sv): The falsifiability point is key. If you can't trace a score back to actual evidence, it's just ... ... learn. Comment from Jim Jeffers(@jim_jeffers): The hard part is making the evaluation falsifiable, not just structured. A score is useful only if the team can see which evidence moved it: customer quote, usage pattern, support ticket, competitor

... many features Too many dependencies Too much history And decisions start getting made with partial context. Have you felt that moment? When your product became too big to fully understand ? We think this is where new tools (like Athena) need to step in - not just to manage, but to reconstruct understanding. Comment from Ng Jun Sheng(@ng_junsheng): The "too many features" part is obvious but the dependencies problem is where it actually gets dangerous. You can still understand ... ... break. Keeping the why close is key- that context gets lost fast. And +1 on AI , it only works if it reflects reality, not just the plan. That s exactly the gap we re trying to close with Athena

... struggle to generate ideas. They struggle to choose the right ones. Discovery produces insights. But decisions still rely on partial context, bias, and pressure. The bottleneck isn t finding opportunities - it s knowing which ones are actually worth building. Athena is built around this gap - not just surfacing ideas, but helping teams evaluate and decide with full context ...

... slightly uncomfortable question: Are we still doing product discovery - or mostly validating decisions we already made? As teams grow, processes get heavier, but it sometimes feels like real exploration gets lost. We ve been thinking about how Athena could push teams back toward actual discovery - not just confirmation. How honest do you think discovery really is today? Comment from Maya Elor(@maya_elor): @rvalenz  I really relate to what you re saying, especially the idea that we probably never ... ... disprove what you already believe - then it s probably not real discovery anymore, or you need to pause and rethink what you re actually trying to build. And this is also exactly the space we tried to solve with Athena

... building Athena as a system that tries to connect product intent with technical reality using AI subagents. Instead of just managing tasks, it tries to understand how the product actually behaves - architecture, constraints, and decision history. Before we go deeper: If you could give an AI workspace one ability related to product understanding, what would it be? Would love to hear different perspectives from PMs, engineers, and founders. Comment from Maya Elor(@maya_elor): @emre_yilmaz_easyparser  Thanks, glad ... ... liked the topic! On your question - Athena

... more and more in product decisions. But here s something we ve been thinking about: When AI is wrong about your product - who notices first? The PM? The engineer? The user? Or worse - no one? As we build Athena, we keep asking ourselves how a system can stay grounded in reality, not just generate convincing answers. Curious how teams think about this - where should the source of truth live in an AI-driven workflow? Comment from Merit Mohammed(@merit_mohammed ... ... perfect name for it. And you're right - the user notices first, they just vote with their feet instead of their words. The triangle is a great mental model. We're trying to build exactly that calibration layer into Athena

... drift from real user signals is exactly what we keep seeing. What s interesting is that it s rarely just a data problem, the data exists, but the decision layer can t keep up with it at scale. With Athena, we re trying to keep it continuous so it evolves with the product as teams scale, instead of relying on that initial snapshot. Comment from Maya Elor(@maya_elor): @sk_uxpin  This is spot on! that translation layer between ... ... things start to distort. At scale, discovery almost becomes a game of broken telephone. The challenge is keeping the original signal intact all the way to the build phase, which is exactly what we re trying to do with Athena

... Hello! I'm Athena. CtrlAltCmd is a digital laboratory for the modern consciousness. We build tools to help you navigate the intersection of AI and human identity. Key Features: Mind OS Debug Kit: Frameworks for mental architecture optimization. Custom GPTs: System Insights: Archived transmissions on AI and the Shadow Self. Neural Protocols: Interactive tools for cognitive calibration. Debug your identity. More coming! Athena

... Lessons from Athena s surprising coverage and what founders can learn about finding the right reporter, framing stories, and pitching press The Wall Street Journal rarely covers seed-stage startups let alone one raising just $2.2M. That s why I was surprised to see Athena

... previous launch, not my browser history -1. Comment from Chris Messina(@chrismessina): @rohanrecommends  I agree with you about feeling overwhelmed. There's now so much information coming at me... that it's hard to tell what's new vs old. The information hierarchy feels too flat. Comment from Chris Messina(@chrismessina): @laura_cruickshanks  it's based on whether there's been one or more launches for the same product. Comment from Chris Messina(@chrismessina): @laura_cruickshanks   (that ... ... will get fixed soon. Comment from Rags(@ragsontherocks): @learnxdesigner   @rajiv_ayyangar   FYI this is what I'm seeing -> there are no left/right arrows ... Comment from Rags(@ragsontherocks): One more UX confusion feedback -> with the Athena