I’ve been watching the AI productivity space, and more granularly about Thought Processing, with a mix of fascination and, I’ll admit, a touch of obsession lately. The past 30 days have delivered some genuinely game-changing developments that I think deserve more attention than they’re getting. Let me walk you through what’s happening and why it matters.
Ambient Intelligence Has Arrived—And It’s Mind-Blowing
If you’ve been following my writing, you know I’ve long predicted that AI would eventually shift from reactive to proactive—and friends, that future is now knocking on our door. Hedy AI’s latest release (version 2.6) introduces what they’re calling “Automatic Suggestions,” but that understated name masks what’s actually happening: your AI assistant is now actively monitoring your conversations and jumping in with insights before you even think to ask.
This isn’t just another feature—it’s a fundamental shift in how we interact with technology. Remember when we transitioned from command-line interfaces to graphical ones? This feels equally significant. The AI is no longer waiting for your prompt; it’s becoming a true participant in your workflow.
Beyond this breakthrough, Hedy has rolled out a suite of practical improvements—session merging for those marathon meetings, bulk operations for the organizationally obsessed (raising my hand here), and custom vocabulary training that finally understands industry jargon without tripping over itself.
The Collaborative AI Revolution Is Here (And Just Raised $43M)
Meanwhile, Granola—once positioned as a personal productivity tool—has made a decisive pivot toward team collaboration with their 2.0 release. Backed by a fresh $43M Series B at a $250M valuation (not too shabby in this funding environment), they’re betting big that the future of AI productivity isn’t individual but collective.
What strikes me about Granola’s evolution is how it mirrors the trajectory we saw with early document tools. Remember when Google Docs disrupted Microsoft’s stranglehold by making collaboration native rather than bolted-on? Granola is attempting the same play in the AI notes space—shared workspaces, team-based AI chat, and searchable collective knowledge.
The implications here are fascinating. When AI can access and learn from your entire team’s conversations and context, the value compounds exponentially. It’s the difference between individual intelligence and organizational intelligence—and that’s where the real productivity breakthroughs happen.
The Quiet Professionalism of Steady Improvers
Not every company is chasing headline-grabbing features, though. I’ve been particularly impressed with Shadow’s approach—dedicating over half their resources to stability improvements rather than feature bloat. Their CEO Jay has been personally reaching out to users (myself included) seeking feedback on what actually matters.
There’s something refreshingly mature about this approach. In the early gold rush days of a new technology category, everyone scrambles to plant their flag on new feature territory. But as markets mature, reliability becomes the true differentiator. Shadow seems to understand this intuitively.
Similarly, Grain continues to focus on incremental improvements to their core experience—better meeting summaries, AI-generated follow-up emails, and workflow optimizations. But what’s almost more exciting is how Grain deployed an MCP and instantly, my entire history of conference calls that I’ve “Grained” over the years, became one rich library of information. They’re doing this with Claude, Cursor, Windsurf, and other clients (ChatGPT coming soon) to work with all your meeting data—research, analysis, reports, drafting deliverables. Here’s how to use it. My take is that Grain’s MCP integration in Claude seems the moset advanced as it includes built-in prompts to run one-click reports, such as a weekly “Voice of the Customer” report to track feedback across all your workspace’s calls. So far, everything is working as promised, which, let’s be honest, is what revolutionary is all about in the software world.
The Consolidation Is Coming
Looking at the broader landscape, we’re seeing the classic signs of a maturing market. SuperWhisper remains the premium choice for Mac dictation but faces increasing pressure from value-oriented competitors like VoiceInk. Cleft Notes continues flying somewhat under the radar despite Fast Company recognition. And Magical (timeOS) is innovating around video clips and enhanced meeting insights. They’ve taken a page out of Grain’s book here, but the superpower of Magical is what you can do with their AI query agent and how it gives you almost always the answers, content or context you need.
What does this all mean? We’re entering the consolidation phase. The initial explosion of AI productivity focused Thought Processing apps are giving way to a more focused competition around specific value propositions. I expect we’ll see significant M&A activity in this space over the next 12-18 months as the stronger players absorb complementary technologies and talent.
What This Means For You
If you’re trying to stay ahead of the curve (and if you’re reading this, I suspect you are), here’s my practical advice:
1 Pay attention to ambient intelligence — Hedy’s proactive suggestions represent the future of AI assistance. This shift from reactive to proactive will fundamentally change how we work.
2 Think team, not individual — Granola’s bet on collaborative AI aligns with where the real value lies. Individual productivity gains are nice, but organizational intelligence is transformative.
3 Prioritize reliability — The companies focusing on stability (Shadow, Grain) rather than feature bloat are building for the long game. In a category where trust is paramount, this approach wins.
4 Prepare for consolidation — The days of dozens of competing AI productivity apps are numbered. The winners will be those who either establish dominant positions in specific niches or build platforms that others can build upon.
What fascinates me most about this moment is how it echoes previous technological transitions I’ve witnessed. The pattern is familiar: explosion of options, followed by feature competition, followed by reliability focus, followed by consolidation. But the compressed timeframe is unprecedented—we’re seeing in months what previously took years.
I’m curious—which of these developments do you find most compelling? Are you leaning toward the ambient intelligence breakthrough, the collaborative approach, or the steady reliability players? The choices we make now as early adopters will help shape where this market goes next.
Until next time,
Andy Abramson