Developer Tests Own AI Planning Engine Against Prompt Injection — Architecture Holds

A developer building PlannerCritic, an open-source engine that pairs one LLM to write plans with a second to review them, ran a structured adversarial test to find security weaknesses in the system. Eleven adversarial goals, 21 injection traps, and 35 regression tests were used, including attempts to bypass MFA, exfiltrate customer data, and override the engine via embedded system commands. In each case, the engine escalated and blocked the requests — not by detecting malicious intent, but by evaluating structural flaws like missing preconditions and weak rollback plans. The critic LLM audited plan structure independently, ignoring injected instructions, while deterministic gates processed logic rather than natural language. The developer concluded that the engine's resilience stemmed from its architecture rather than any LLM-level cleverness, though acknowledged that open seams in the system still remain.

Awarapan 2 nears Rs 140 crore India net in 11 days, logs 202% profit

Emraan Hashmi's Awarapan 2 has emerged as one of Bollywood's biggest hits of 2026, approaching the Rs 150 crore mark at the domestic box office. The film achieved this milestone within just ten days of its release, surpassing the profit margins of the earlier franchise entry Murder. It has now ranked as the fifth-highest-grossing Bollywood release of the year. The sequel marks a strong commercial comeback for Emraan Hashmi, recording a 202% return on investment.

AWS Deploys Multi-Agent System to Cut Cloud Migration from Weeks to Minutes

AWS Professional Services has published production data on a deployed multi-agent system that dramatically reduces infrastructure-as-code development time for enterprise cloud migrations. The system chains four specialized AI agents — handling discovery, IaC generation, governance, and post-migration operations — built on Amazon Bedrock AgentCore primitives. Agents communicate through immutable artifacts stored in S3 and state transitions tracked in DynamoDB, avoiding circular dependencies by never calling each other directly. A portfolio governance agent acts as the sole gatekeeper, running cost, security, and compliance checks before any migration can proceed. If templates fail validation, the workflow halts and the IaC generation agent must resolve all issues before the process can continue.

HyperFrames Turns HTML and GSAP Animations Into Deterministic MP4 Files

HyperFrames is an open-source TypeScript framework developed by HeyGen that converts HTML, CSS, and GSAP animations into frame-perfect MP4 video files via a command-line interface. The tool chains Puppeteer for headless browser rendering, GSAP for deterministic animation timing, and FFmpeg for video encoding, ensuring the same HTML input always produces identical output. Unlike conventional video tools designed for human designers, HyperFrames treats video as a build artifact, making it suitable for AI agents that require structured, reproducible outputs. It integrates with AI workflows through an MCP server and a skills.sh distribution, allowing coding agents to invoke video rendering as a native capability. The project has gained significant traction on GitHub, accumulating 42,000 stars and ranking among the top trending TypeScript repositories.

How to Design Startup, Readiness, and Liveness Probes for Cleaner App Health

For Node.js applications running in Docker or Kubernetes, engineers recommend assigning distinct roles to each of the three health probes: startup, readiness, and liveness. The startup probe should confirm that one-time initialization tasks, such as loading and compiling pricing rules, are complete before other probes activate. Readiness should reflect whether an instance can safely handle live traffic at any given moment, while liveness should only check for conditions a container restart can actually fix, such as a stalled event loop. Placing dependency failures like an unreachable database into liveness probes can trigger unnecessary restart storms, turning a single outage into a capacity crisis. Keeping routine health-check traffic out of application logs and tracking state transitions rather than every successful poll helps maintain meaningful metrics.

Why AI Agents Break in Production: Memory, Testing, and Tooling Failures Explained

AI agents that perform well in development often fail in production due to three core engineering gaps: memory leakage, evaluation blindness, and tooling fragility. Memory leakage occurs when agents accumulate unbounded conversation history, causing context windows to overflow and degrading reasoning quality. Evaluation blindness refers to the absence of deterministic testing frameworks, leaving developers unable to catch regressions before deployment. Tooling fragility involves unhandled error states and race conditions that destabilize agent workflows under real-world conditions. Addressing these gaps requires architectural discipline, including hybrid memory systems, golden dataset evaluations, and robust error-handling patterns.

Developer Shares Minimal GitHub Actions CI/CD Pipeline With Secrets and Rollback Tips

A software developer has outlined a streamlined CI/CD pipeline using GitHub Actions, designed to address gaps commonly found in beginner tutorials such as secret management, dependency pinning, and rollback handling. The pipeline consists of three stages — test, build, and deploy — triggered on pushes and pull requests to the main branch. Credentials like server host, SSH username, and private key are stored as GitHub repository secrets rather than hardcoded in the workflow file. Built files are transferred to a remote server via SCP, while a simple tarball-based backup system allows quick rollbacks if a deployment breaks. The author emphasizes using a dedicated deploy user with limited server permissions and locking dependency versions to avoid environment inconsistencies.

Developer's AI Cost Tracker Silently Logged Zeros for 52 Days Due to Hook Bug

A developer building an autonomous AI-powered business discovered that their Claude Code cost-tracking system had been logging zero values for every session across 52 days and 2,340 log entries. The silent failure stemmed from a flawed assumption in the Stop hook script, which expected token usage and model data to arrive via stdin — fields that the hook's payload does not actually include. The bug went undetected because the logs appeared to be recording normally, producing no errors or alerts. The developer resolved the issue in a second version of the script by reading cost data directly from Claude Code's session transcript files, which reliably contain model and usage information. The case highlights a key risk in autonomous AI workflows: silent data errors can persist far longer than outright failures, which are easier to catch and fix.

A Successful YouTube Upload Left No Local Record, Enabling Silent Duplicates

A developer building an automated YouTube video pipeline discovered a critical flaw where a failed post-upload verification step prevented a local record file from ever being written, even though the video had already been successfully uploaded. Because the duplicate-upload guard relied solely on the existence of that local file, re-running the pipeline would bypass the check entirely and upload the same video a second time. The bug was compounded by a second blind spot: five earlier videos uploaded via a separate tool had never created the required record files, leaving those episodes invisible to the guard from the start. All existing unit tests passed throughout, as none verified the on-disk state left behind after an exception. The root cause was not faulty guard logic but the absence of a shared bookkeeping contract across two independent upload paths.

Kidney Disease Can Progress Silently; Early Tests and BP Checks Are Key

Kidney disease often advances without obvious symptoms, making early detection difficult. Common warning signs can include swelling, fatigue, and changes in urination patterns. High blood pressure is closely linked to kidney health and requires regular monitoring. Routine blood and urine tests can help identify kidney problems before significant damage occurs, according to medical experts.

Python Tutorial Shows How to Build a Qualified YouTube Creator Prospecting Tool

A new tutorial published on DEV Community demonstrates how to build a YouTube channel finder in Python that goes beyond basic name or topic lookups. The tool is designed for use cases such as sponsor outreach, educator recruitment, or selling services to creators, by filtering candidates based on niche, upload frequency, subscriber count, and recent viewership. Using the Apify client library, the workflow discovers channel candidates, analyzes recent performance metrics, and returns structured data rows per channel without requiring a manual review of each profile. Key output fields include recent median views, estimated videos per month, content format ratios, inferred country data, and publicly available business contact information. The tutorial argues that qualifying active channel state — rather than relying solely on lifetime subscriber totals — is what separates a basic scraper from a practical creator-prospecting dataset.

Trump Held Call With Pakistan Army Chief Last Week, Discussed Iran

US President Donald Trump spoke with Pakistani Army Chief General Asim Munir last week, according to a CNN report. A source familiar with the conversation confirmed the two discussed the topic of Iran during the call. The discussion took place ahead of Trump's visit to Iran, suggesting diplomatic groundwork was being laid. The call highlights Pakistan's potential role as a back-channel or intermediary in US-Iran relations.

Why Passwork built a three-tier recovery system instead of an admin master key

Password manager Passwork has detailed how it designed account recovery without a single 'god mode' credential that could decrypt all stored data at once. The company argues that any backdoor capable of unlocking everything instantly becomes a critical single point of failure, turning one compromised account into a total breach. Instead, Passwork uses a zero-knowledge architecture where the server only stores encrypted data and never holds decryption keys, meaning recovery must be planned before an incident occurs. To handle lost access, the system splits recovery into three isolated tiers, each limited to a narrow task, so no single layer can expose the entire vault. The first tier addresses owner login issues via server-level CLI commands that are disabled by default and require explicit activation, keeping them out of reach of web-only attackers.

TikTok Creator 'Mama A' Alyshia Rushing, 26, Dies in Alabama Car Crash

Alyshia Rushing, a 26-year-old TikTok content creator widely known as 'Mama A,' died on August 22 following a two-vehicle collision in Montgomery, Alabama. A second person, Landon Dunn, also lost his life in the same crash. Montgomery police have opened an investigation into the incident. Rushing is survived by four children, who have been left without their mother. A GoFundMe campaign has since been launched to help the children and their father cover essential expenses including housing, schooling, childcare, and counseling.

Dallas Cowboys Cheerleaders Director Kelli Finglass Reflects on Future and 35-Year Career

Kelli Finglass, director of the Dallas Cowboys Cheerleaders, has opened up about her 35-season tenure with the iconic squad. She reflected on how her leadership philosophy has evolved, noting that vulnerability has grown more meaningful to her than the pursuit of perfection. Finglass credited television exposure for helping audiences connect with the cheerleaders as individuals beyond their performances. She also acknowledged that retirement is a possibility she has considered, with family priorities and the prospect of becoming a grandmother potentially shaping her next chapter.

Brand Mentions in AI Search Are Three Distinct Signals, Not One

As more buyers turn to AI tools like ChatGPT and Perplexity instead of traditional search engines, brands are increasingly asking whether these systems mention them in responses. However, experts argue that 'being mentioned' actually encompasses three separate and independent signals: appearing by name in the generated prose, being linked as a cited source, and being cited accurately. A brand's domain can appear in source citations without its name ever appearing in the answer text, meaning a name-only check can produce misleading results. Even more critically, an AI engine can both name and cite a brand while stating outdated or incorrect information, such as a retired price or a misattributed feature. Each failure state requires a different fix, making it essential for brands to measure all three signals rather than treating AI mention as a simple yes-or-no question.

AI Agents Handle Tasks But Humans Still Bridge the Gaps Between Them

A software developer argues that most AI automation pipelines still rely on humans to manually pass information between tools — copying logs into AI chat windows, then pasting outputs into Jira, for example. While individual tasks like code review or log analysis are increasingly handled by AI agents, the workflows connecting those tasks remain largely manual. The author contends that teams only truly need human judgment at two points: confirming the goal at the start and verifying the outcome at the end. A key gap identified is agent memory — once an AI agent completes a task, the context and findings it built up are often lost rather than passed forward automatically. As APIs already connect most developer tools like AWS, GitHub, and Jira, the author believes fully automated end-to-end workflows are the logical and near-term next step.

EAM Jaishankar meets Russian President Vladimir Putin, focus on trade, energy, fertilisers, high-tech

330 victims, Rs 400 crore: Goa digital arrest leads ED to pan-India network of cyber fraudsters

Government on US Ambassador Sergio Gor’s remarks: Donald Trump unpredictable, so took cautious approach