Build, discover, and monetize AI agents.

Okta rolls out Agent SSO so AI agents can log in like employees

What changed: Okta launched Agent SSO, a new capability that lets AI agents be treated as identities inside Okta’s Universal Directory and managed with the same access controls used for human staff. Agent SSO brings Okta’s Cross App Access protocol into its identity platform so supported AI agents can be registered, assigned policies, and given short‑lived tokens instead of hard‑coded credentials or overly broad access.

Why it matters: As teams deploy agents that act across SaaS tools and internal systems, centralized identity and access management becomes essential to avoid a sprawl of fragile API keys and shadow accounts. This launch makes it easier for security and IT teams to answer basic questions like where agents run, what they can reach, and who approved that access.

Try/watch: If you already use Okta, inventory any agents touching production systems and pilot Agent SSO for one high‑value workflow, then watch how short‑lived tokens and policy reuse change your access review and incident‑response playbooks.

Keenable raises $26M to power live‑web search for AI agents

What changed: Keenable exited stealth with a $26 million seed round led by Accel to provide web search infrastructure tailored for AI agents. The company has built a 100‑billion‑document index and a Search API already running in production with multiple AI labs and inference providers, plus an official Model Context Protocol (MCP) server that gives agents keyless access with up to 1,000 requests per hour. Keenable offers tiered pricing, from a free keyless tier for prototyping to higher‑throughput plans for large‑scale deployments.

Why it matters: Many agents still struggle with slow, unreliable web tools; a search stack optimized for how agents retrieve and reason over documents can reduce latency and hallucinations while improving task completion rates. Builders get a ready‑made MCP endpoint and scalable pricing curve instead of operating their own crawlers and indexes.

Try/watch: If you maintain an MCP‑based agent, experiment with Keenable’s keyless server as a drop‑in live‑web backend, then track changes in task success, latency, and cost versus your current search setup.

Aderant opens early access to specialized AI agents for law‑firm operations

What changed: Legal business software vendor Aderant launched early access to its Agent Center, giving law firms the ability to deploy purpose‑built AI agents for billing, collections, compliance, forecasting, and rate management. The initial portfolio includes agents focused on appeals, collections, talent evaluation, time‑entry quality, outside counsel guideline compliance, general ledger forecasting, and billing rates, all designed to work within Aderant’s Stridyn platform and MADDI AI layer.

Why it matters: Instead of generic chatbots, firms get task‑specific agents embedded in existing financial and practice‑management workflows, which can shorten cash cycles, tighten compliance, and standardize evaluations. For leaders under fee pressure, these agents offer a way to automate back‑office work without rebuilding systems or retraining lawyers on unfamiliar tools.

Try/watch: Identify one bottleneck—such as collections or time‑entry cleanup—where Aderant already has an agent, enroll a small practice group in the early access program, and measure changes in write‑downs, realization, and staff hours before scaling further.

Temporal report shows 70.8% leap in AI agent use among engineers

What changed: Temporal released its 2026 State of Development Report: AI Agents, based on a survey of more than 550 engineers and engineering leaders in the US and UK. The report finds that 80.8% of respondents now use AI agents daily or more, up from 47.3% a year earlier—a 70.8% relative increase in frequent use. The study also documents where deployments succeed and where agentic applications still break down for engineering teams.

Why it matters: The data confirms that AI agents have moved from experiments to daily tools for most surveyed engineering organizations, which raises expectations around reliability, observability, and governance. Teams that still treat agents as side projects risk falling behind peers who are systematically redesigning workflows around them.

Try/watch: Use the report’s adoption benchmarks to baseline your own usage, then pick one engineering workflow—like incident response, CI/CD, or backlog grooming—to redesign as an agent‑first flow with clear ownership, metrics, and roll‑back paths.