The Git Times

Supabase, the open-source Postgres platform mirroring Firebase's developer experience, has shipped key Pro-tier enhancements amid its v1.26.03 release. These updates target production workloads, with Log Drains now routing Postgres, Auth, Storage, Edge Functions, and Realtime logs to destinations like Datadog, Grafana Loki, Sentry, Axiom, S3, or custom endpoints. This closes a gap for teams monitoring distributed apps without custom piping.

Documentation has also gone AI-native: every guide on docs.supabase.com now offers a "Copy as Markdown" button, plus direct prompts for ChatGPT and Claude. Developers can ingest full pages into agents or tools instantly, streamlining prototyping. A related webinar, "Ship Fast, Stay Safe," guides agencies on balancing AI coding velocity with Supabase controls for production deploys.

Storage sees a major performance and security overhaul, boosting throughput and hardening access—critical for file-heavy apps. These build on Supabase's core stack: a dedicated Postgres instance with extensions like pgvector for embeddings, PostGIS for geospatial, and PostgREST for instant REST/GraphQL APIs. Realtime, an Elixir server, pipes database changes via WebSockets using Postgres replication. Edge and database Functions handle compute, while Auth covers OAuth2 and beyond.

Self-hosting remains viable with Docker or local dev, but the hosted platform dominates for speed. Supabase prioritizes MIT/Apache-licensed tools—building what's missing, like its vector toolkit. No Firebase 1:1 clone; it's Postgres-first for reliability after 30+ years of evolution.

For builders, this matters now as AI integrations explode. Log Drains enable observability at scale, Markdown docs feed agentic workflows, and Storage fixes cut latency. Agencies hitting production walls with Firebase alternatives get enterprise signals without vendor lock-in.

• Pro users: Drain logs externally for alerting and compliance.
• AI devs: Export docs to fine-tune agents on Supabase patterns.
• Storage-heavy apps: Leverage optimized buckets with RLS enforcement.

Community channels—Discord, forums, GitHub Issues—keep momentum high. Watch releases for vectors and realtime polish.

Drake, the open-source C++ toolkit for model-based design and verification in robotics, has shipped v1.51.1, its latest release as of March 2026. Long a staple for developers tackling multibody dynamics, simulation, and control, this update zeroes in on the mathematical program toolbox by incorporating a pre-compiled version of SNOPT.

SNOPT, developed by Philip E. Gill and Elizabeth Wong, is a battle-tested sparse nonlinear optimizer. Binary releases now bundle it directly, sparing builders the hassle of separate compilation and licensing hurdles. This lands in Drake's solvers group (doxygen_cxx/group__solvers.html), where it joins tools for linear, quadratic, and nonlinear programming.

For robotics engineers, the change matters in workflows demanding precise trajectory optimization or constraint satisfaction. Drake models systems as diagrams of interconnected components—rigid bodies, contacts, actuators—then verifies them against specifications like stability or collision avoidance. SNOPT's integration accelerates solving large-scale problems, such as optimizing humanoid locomotion over uneven terrain or grasping in cluttered spaces.

Consider a legged robot: Drake simulates hybrid dynamics with unilateral contacts, formulates mixed-integer programs for footstep planning, and uses SNOPT to minimize energy while respecting torque limits. Pre-compilation cuts setup time, letting developers iterate faster in CI/CD pipelines or real-time tuning.

Release notes highlight no breaking changes, preserving backward compatibility. Builders on Linux, macOS, or Windows get seamless access via Bazel or CMake builds. The toolbox now supports more solvers out-of-the-box, aligning Drake with demands for verifiable autonomy in industrial arms, drones, and mobile manipulators.

Why now? As robotics shifts toward certified systems—think warehouse automation or surgical robots—embedded optimization lowers barriers to rigorous verification. Drake's documentation (drake.mit.edu) details usage, with examples in C++ and Python bindings.

This isn't a overhaul but a pragmatic boost, ensuring Drake remains indispensable for those engineering provably safe behaviors in uncertain environments.

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Builders revisiting the ESP32-BlueJammer will find its latest release a significant upgrade for security testing and controlled 2.4GHz disruption. Originally launched in mid-2024, the project—using an ESP32 microcontroller paired with dual nRF24L01+PA+LNA modules—generates noise and floods the 2.4GHz spectrum with junk packets. This interrupts Bluetooth audio, BLE connections, WiFi networks, RC drones, IoT gadgets, wireless peripherals, and more, with a baseline range exceeding 30 meters on stock antennas.

The new ESP32-BlueJammer-official release introduces formal support for a dedicated PCB design, streamlining assembly for tinkerers. Key additions include:

• Ultra-precise battery voltage readout and a top-right corner indicator on the 0.96" I2C OLED display.
• USB power detection alongside battery charging status, complete with an animated charging icon.
• A web-based flasher at https://esp32-bluejammerflasher.pages.dev for effortless firmware deployment.

Hardware remains DIY-friendly. The reference ESP32-RF DIY-PCB accommodates an ESP32-WROOM-32U/E DevKitC, two nRF24 modules, the OLED, LEDs, and slide switches. Essentials include 10-100µF capacitors (x2), specific resistors (1kΩ for R1, 47kΩ for R2/R3/R5/R7, 100kΩ for R4/R6), and optional TP4056 charging with a 3.7V Li-Ion cell via JST PH 2.0. Range boosts come from larger antennas or 2.4GHz amplifiers, but the project stresses educational use only—jamming violates regulations in most jurisdictions.

Technically, it leverages the ESP32's processing for packet generation and nRF24's RF output to blanket the band, differing from narrowband tools by targeting the entire 2.4GHz broadband. The v2 changelog (viewable via GitHub compare) details these refinements, building on prior BlueJammer-V2 iterations and ports like BW16-BlueJammer or Flipper Zero's ZeroWave.

For developers, this matters now as IoT proliferation heightens interference testing needs. The webflasher lowers barriers, while battery smarts enable portable field use without constant monitoring. Schematics, 3D cases, and channel demos remain in the repo, supporting ethical pentesting workflows.

Who cares? Hardware hackers refining drone defenses, cybersecurity pros auditing BLE stacks, and ESP32 enthusiasts prototyping resilient networks. The update solidifies its role in the growing ecosystem of affordable RF disruption tools.

Union's latest v1.2.3 release, tagged as bundle-union-1/v1.2.3, packages pre-built binaries for x86_64 and aarch64 Linux architectures, complete with SHA256 checksums for verification. This streamlines deployment of its zero-knowledge bridging protocol, eliminating the friction of compiling multi-language components from source.

At its core, Union enables trust-minimized message passing via Consensus Verification, eschewing oracles, multisignatures, or MPC. It supports IBC for Cosmos chains and bridges to EVM environments like Ethereum, Arbitrum, and Berachain. The protocol's galoisd prover, built in Go with Gnark, generates succinct ZK proofs of state consensus, while the Rust-based voyager relayer handles modular, high-throughput packet relay across ecosystems.

Key components include:

• uniond: Go-based node using CometBLS for consensus.
• cosmwasm: Rust smart contracts for CosmWasm compatibility.
• evm: Solidity contracts for EVM chains.
• unionvisor: Rust supervisor for production node management.
• light-clients: Rust implementations verifying foreign chain states.

Decentralized governance controls upgrades, connections, and token configs, aligning protocol evolution with validators and users. Developers can bootstrap via Nix for reproducible builds—curl the installer, then enter a dev shell with all dependencies pinned. macOS users get OrbStack guidance for Linux-only components.

This release matters now as DeFi demands censorship-resistant bridges amid rising chain fragmentation. Union's ZK proofs ensure extremely high security without third-party trust, critical for asset transfers, NFTs, and general messaging. Production bundles lower barriers for operators running full nodes or relayers, especially with drip faucet integration at app.union.build/faucet.

For builders, v1.2.3 accelerates integration via the TypeScript SDK, enabling apps at app.union.build (Svelte/TypeScript) and docs at union.build (Astro/TypeScript). Extract the tar.gz (e.g., 3910cf200a6a5cb31ff6c7c4abbba4b1a0580b086cee5bada659ede22c106122 for x86_64), verify checksums, and deploy—signal for scaling interoperable dApps without compromise.

The Sesame Robot project has leveled up its toolkit with Sesame Studio, a dedicated animation composer that streamlines creating custom quadruped behaviors on the ESP32 platform. This addition, alongside the Sesame Companion App, shifts the project from basic locomotion demos to a robust framework for expressive robotics.

At its core, Sesame relies on eight servo motors—two per leg—for 8 degrees of freedom, enabling stable walking, waving, and dancing. The 128x64 OLED display renders reactive faces that sync with actions, pulling from an emotion library with talk variants suited for voice integrations. All structural parts print in PLA with minimal supports, keeping costs at $50-60 including the ESP32 board.

What sets the recent evolution apart is Sesame Studio's drag-and-drop interface for sequencing keyframes. Builders sequence leg poses, head tilts, and face emotes into fluid animations, exporting directly to the robot's firmware. No more trial-and-error CLI tweaks; import via the serial interface or web UI.

Network features shine here: WiFi connectivity exposes a RESTful JSON API, letting Python or JavaScript scripts trigger emotes remotely. Example: POST /api/emote/wave with parameters for speed and intensity. The Companion App, a Python CLI tool, adds voice control via speech-to-text, bridging to assistants like those on Raspberry Pi setups.

Firmware includes debugging modes for servo calibration and gait tuning, with pre-programmed routines like pointing and resting as starting points. Wiring guides and CAD/STL files cover inverse kinematics basics, assuming Arduino IDE familiarity.

For builders, this matters amid rising demand for affordable IoT pets. Sesame sidesteps pricier alternatives by embedding API access, fostering integrations like swarm coordination or AR teleoperation. Discord discussions highlight users chaining animations for patrol behaviors.

The March push refined API stability and Studio exports, fixing edge cases in multi-leg coordination. With serial CLI for rapid testing (sesame walk --speed 0.5), it's primed for classroom prototypes or home automation hacks.

This iteration cements Sesame as a gateway to legged robotics, emphasizing software over hardware complexity.