Feedly vs Deepnote
Side-by-side trajectory, velocity, and editorial themes.
Feedly's cyber-threat-intelligence engine grows through steady coverage and enrichment additions.
Feedly has settled firmly into cyber and market threat intelligence, shipping a biweekly changelog aimed at CTI and analyst teams. Recent releases add analyst-usable output (Suricata detection rules pulled straight from Insights Cards), broader vulnerability and exploit coverage (Oracle and Atlassian advisories, exploit-type tracking), and third-party enrichment (GreyNoise, VirusTotal, Analyst1), alongside a smarter Insider Threats AI model and an Ask AI Research Playground for evaluators.
The arc is deepening the intelligence graph and making its output directly operational: more sources and advisories feeding the model, richer IoC context via enrichment integrations, and AI features (Ask AI, Cyberattack Agent, insider-threat models) that sit on top of that data. The feed also carries near-duplicate entries for the same release, a crawl artifact rather than shipping cadence.
Expect continued coverage expansion (more advisory sources, enrichment partners) and incremental AI-research tooling on the biweekly cadence, with no single directional pivot signaled in these entries.
Deepnote reshapes the data notebook into agent-operable infrastructure.
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
Two tracks are converging: reproducibility and engineering rigor (immutable run snapshots, Git sync, notebook interoperability) and agent-operability (MCP tools, Codex context). Deepnote is positioning the workspace as the trusted context layer that AI agents act through, not just a place humans write notebooks.
Expect more MCP tooling that lets agents operate Deepnote projects autonomously, plus deeper native hooks for external coding agents — the workspace-as-agent-context bet will likely expand beyond Codex.
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