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01AI Development AgencyCustom AI agents, copilots & automation02AI ServicesAgentic AI services and platforms03Custom MVP DevelopmentMVP and product development04UI/UX DesignProduct design & branding05Software Staff AugmentationScale your engineering team06ServicesView all our services
01TechCrunchEnterprise blogging platform02State AffairsAI-powered policy intelligence03WyndMobility platform MVP04EquooMental health gaming app05ImmaginnTalent showcase platform06AjenticAI-powered CRM system07RainbowEdTech learning platform
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Blog/AI & ML

AI & ML

All PostsAI & AutomationAI & MLDevOpsIndustry SolutionsMarketingOtherSoftware DevelopmentTeam & HiringTechnologyWeb Development
Diagram of an AI agent receiving System Instructions, Tool Descriptions, Retrieved Evidence, Memory, Task State, and Examples shaped by Select, Order, Compress, and Refresh before producing answers an15 MIN
AI & ML

Context Engineering: Optimizing AI Agent Performance for 2026

Learn how context engineering shapes AI agents' performance, addressing issues of reliability and cost. Discover effective strategies for implementation.

Ankit Kumar BaralAnkit Kumar Baral2026.10.08
Split workflow diagram showing UI agents clicking through browser screens and API agents connecting directly to CRM, ERP, database, and storage across reliability, latency, security, maintenance, obse15 MIN
AI & ML

UI Agents vs API Agents: Choosing the Best for AI Automation

Dive into the comparison of UI agents and API agents for AI automation, exploring trade-offs, use cases, and choosing the best interface for your needs.

Naresh HRNaresh HR2026.10.07
Layered diagram with many agents connected to inventory, identity, policy, tracing, evaluation, approvals, budgets, and kill switches above models, tools, APIs, and data sources15 MIN
AI & ML

Agent Control Plane: Centralized Governance for AI Agents in 2026

Explore the importance of an agent control plane when managing numerous AI agents and ensure better governance and control.

Ankit Kumar BaralAnkit Kumar Baral2026.10.07
Operational dashboard with token ceiling, model calls, tool calls, monetary cap, retry budget, downgrade rules, and termination status for an active agent task13 MIN
AI & ML

Agent Budget Control: Advanced Techniques for Production 2026

Learn how to implement layered budget controls for agents to prevent overspending and ensure efficient task completion in production environments.

Ankit Kumar BaralAnkit Kumar Baral2026.10.06
Architecture diagram with a 30 second budget bar, orchestrator, layered deadlines, cancellation icons, and a partial results panel labeled summary returned and fallback used15 MIN
AI & ML

AI Agent Timeouts: Mastering Workflow Efficiency in 2026

Explore how AI agent timeouts can prevent runaway workflows and enhance reliability, covering deadlines, cancellations, and more!

Naresh HRNaresh HR2026.10.05
Wide system diagram with Client App, API Gateway, Queue, Worker Pool, Job Store, Status API, WebSocket or SSE progress stream, retries, dead-letter queue, cancellation path, and observability dashboar14 MIN
AI & ML

async job processing: Optimize Long-Running Tasks for 2026

Learn how async job processing moves long-running tasks out of HTTP requests, improving reliability and user experience with structured job management.

Ankit Kumar BaralAnkit Kumar Baral2026.10.01
Architecture diagram with client, API layer, durable queue, AI worker pool, state store, status API, WebSocket or SSE progress stream, cancellation endpoint, observability tools, retries, and dead-let13 MIN
AI & ML

long-running AI agents: Efficient Asynchronous Workflow Strategies

Learn how to implement long-running AI agents without blocking HTTP requests. Explore best practices for robust asynchronous workflows.

Naresh HRNaresh HR2026.10.01
Workflow diagram with Order Service, Payment Gateway, Notification Service, and CRM linked by forward and compensation steps, plus labels for irreversible notification, retries, idempotency key, and h14 MIN
AI & ML

Saga Pattern: Agile Recovery for AI Agents in 2026

Discover how the saga pattern empowers AI agents to handle failures across multi-step workflows, improving transaction safety and efficiency.

Naresh HRNaresh HR2026.09.30
Architecture diagram maps conversational context, business state, task progress, tool outputs, scratch data, and human approvals to model memory, database, queue, and workflow engine13 MIN
AI & ML

AI Agent State Management: Effective Strategies for 2026

Explore essential strategies for AI agent state management, separating model memory from durable business states and improving overall efficiency.

Suvam SwainSuvam Swain2026.09.29
Architecture diagram with Sales, Support, Billing, and Workflow agents concurrently updating CRM contact, ticket, invoice, and workflow state records through locks, version checks, idempotency keys, a15 MIN
AI & ML

Agent Race Conditions: Preventing Failures in Workflows 2026

Two agents updating the same CRM record can lead to silent failures. Learn how to prevent agent race conditions in your workflows with best practices.

Naresh HRNaresh HR2026.09.29
Wide system diagram with orchestrator, workflow engine, checkpoint store, idempotency keys, human approval pause, and resume paths after worker crash, restart, and network timeout16 MIN
AI & ML

Durable AI Agents: Workflow Strategies for Resilient Systems

Explore effective strategies for building durable AI agents that can resume safely after interruptions. Say goodbye to state loss and action duplication.

Ankit Kumar BaralAnkit Kumar Baral2026.09.29
Central Tool-Using Agent diagram connected to Retrieved Documents, Websites, Emails, Tool Outputs, and MCP Resources with hostile instruction snippets and security checkpoints labeled Content Sanitiza14 MIN
AI & ML

Indirect Prompt Injection: Testing Strategies for AI Agent Security

Learn about indirect prompt injection testing and explore practical strategies to enhance AI agent security against various attack surfaces.

Naresh HRNaresh HR2026.09.26
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